1,286 results
Search Results
2. Contextual Qualitative Deterministic Models for Self-learning Embodied Agents
- Author
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Lemeire, Jan, Wouters, Nick, Van Cleemput, Marco, Heirman, Aron, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Buckley, Christopher L., editor, Cialfi, Daniela, editor, Lanillos, Pablo, editor, Ramstead, Maxwell, editor, Sajid, Noor, editor, Shimazaki, Hideaki, editor, Verbelen, Tim, editor, and Wisse, Martijn, editor
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- 2024
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3. DISS: A Discrete Input-Space Sampling Path Planning and Obstacle Avoidance Strategy for Swarm Robotics
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Houacine, Naila Aziza, Drias, Habiba, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Drias, Habiba, editor, Yalaoui, Farouk, editor, and Hadjali, Allel, editor
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- 2023
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4. An Architectural Approach for Enabling and Developing Cooperative Behaviour in Diverse Autonomous Robots
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Linkola, Simo, Mäkitalo, Niko, Laurinen, Tomi, Kantosalo, Anna, Männistö, Tomi, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Scandurra, Patrizia, editor, Galster, Matthias, editor, Mirandola, Raffaela, editor, and Weyns, Danny, editor
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- 2022
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5. Developing Intelligent Autonomous Vehicle Using Mobile Robots’ Structures
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Popişter, Florin, Steopan, Mihai, Someşan, Sergiu Ovidiu, Cavas-Martínez, Francisco, Series Editor, Chaari, Fakher, Series Editor, di Mare, Francesca, Series Editor, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Series Editor, Ivanov, Vitalii, Series Editor, Kwon, Young W., Series Editor, Trojanowska, Justyna, Series Editor, Durakbasa, Numan M., editor, and Gençyılmaz, M. Güneş, editor
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- 2022
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6. Multi-robot navigation based on velocity obstacle prediction in dynamic crowded environments
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Chen, Yimei, Wang, Yixin, Li, Baoquan, and Kamiya, Tohru
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- 2024
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7. A robot motion skills method with explicit environmental constraints
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Huang, Yonghua, Li, Tuanjie, Ning, Yuming, and Zhang, Yan
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- 2024
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8. An efficient constraint method for solving planning problems under end-effector constraints
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Wang, Yahao, Li, Zhen, Li, Yanghong, and Dong, Erbao
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- 2024
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9. Special issue on robot and human interactive communication 2023 (selected papers from RO-MAN 2022).
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Gentiane Venture, Kenji Tahara, Natsuki Yamanobe, Shingo Shimoda, and Masahiro Shiomi
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ROBOTS , *HUMAN-robot interaction , *STRAIN sensors , *HUMAN beings , *AUTONOMOUS robots - Published
- 2023
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10. How CPS and Autonomous Robots are Integrated to other I4.0 Technologies: a systematic literature review.
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Venancio Teixeira, Jônatas, da Silva Hounsell, Marcelo, and Wildgrube Bertol, Douglas
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TECHNICAL literature ,AUTONOMOUS robots ,CYBER physical systems ,INDUSTRY 4.0 ,SEARCH engines ,INDUSTRIAL revolution - Abstract
Industry 4.0 (I4.0) brings a set of challenges that need to be settled to enable the expected industrial revolution. Cyber-Physical Systems (CPS) and Autonomous Robots are two of mainstream I4.0 technologies and can be combined with other Enabling Technologies to overcome main I4.0 challenges. This Systematic Literature Review (SLR) aimed to understand how these Enabling Technologies were combined with CPS and Autonomous Robots to achieve fully featured I4.0 solutions. The 5C is a CPS architecture which was used as a measurement to CPS compliance. After filtering and processing 15,144 papers from six different academic search engines, it was found that full 5C compliant solutions are rare to find; that not all enabling technologies were integrated; and most of existing research focused in implementing practical solutions, but comparison to conventional approaches is scarce. We conclude that there is a need for further research to accomplish full 5C I4.0. [ABSTRACT FROM AUTHOR]
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- 2023
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11. Editorial Note for the Special Issue: Perspectives and Challenges in Doctoral Research—Selected Papers from the 10th Edition of the Scientific Conference of the Doctoral Schools from the "Dunărea de Jos".
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Rusu, Eugen and Rapeanu, Gabriela
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DEEP learning ,CONVOLUTIONAL neural networks ,FOOD science ,INDUSTRIAL engineering ,ARTIFICIAL neural networks ,TRIBO-corrosion ,AUTONOMOUS robots - Abstract
This editorial note is dedicated to the 10th Scientific Conference which was held on June 2022 in Galati, Romania, and was organized by the Council of Doctoral Schools of the "Dunarea de Jos" University of Galati (SCDS-UDJG). Three articles in this Special Issue present findings in the field of mechanical and industrial engineering. Four articles present studies related to artificial intelligence technologies, representing the majority of papers published in this Special Issue. [Extracted from the article]
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- 2023
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12. Autonomous exploration through deep reinforcement learning
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Yan, Xiangda, Huang, Jie, He, Keyan, Hong, Huajie, and Xu, Dasheng
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- 2023
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13. Enhanced DWA algorithm for local path planning of mobile robot
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Lai, Xin, Wu, Dan, Wu, Di, Li, Jia He, and Yu, Hang
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- 2023
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14. FAOF: a feature aggregation method based on optical flow for gangue detection on production environment
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Yanzi, Miao, Xiaolin, Wang, Yuanhao, Zhang, Liang, Ji, Yizhou, Wang, and Zhiyang, Xu
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- 2022
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15. A review paper on autonomous mobile robots.
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Poduval, Dhanya R. and Rajalakshmy, P.
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MOBILE robots ,ROBOTICS ,WAREHOUSES ,ENVIRONMENTAL mapping ,AUTONOMOUS robots ,ROBOTS ,SYSTEMS development - Abstract
Robotic technologies are overgrowing with an improvement in their capabilities, such as "autonomy" and "mobility". The two main forces driving these advancements are economics and safety. Often referred to as the "three D's": Dirty, Dangerous and Dull, many tasks performed by humans are either dangerous, such as tactical reconnaissance, or highly repetitive, such as patrolling in an industrial factory. Autonomous Mobile Robots are often well suited to these tasks because they can be more consistent and relatively expendable. These robots have historically been designed to replace humans in these dangerous and dull tasks, which means they are designed with human-like capabilities. There is a growth in the development of intelligent systems based on mobile sensors due to increased demand for automated surveillance of indoor and outdoor environments, such as production plants, airports, warehouses, military etc. The fundamental optimization problems related to environmental map representation, localization, navigation, and surveillance tasks have been addressed entirely in most robotic surveillance schemes. [ABSTRACT FROM AUTHOR]
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- 2022
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16. MoDeT: a low-cost obstacle tracker for self-driving mobile robot navigation using 2D-laser scan
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Nguyen, Toan Van, Do, Minh Hoang, and Jo, Jaewon
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- 2022
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17. A novel tracking system for human following robots with fusion of MMW radar and monocular vision
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Zhu, Yipeng, Wang, Tao, and Zhu, Shiqiang
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- 2022
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18. Map-less long-term localization in complex industrial environments
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Liu, Zhe, Qiao, Zhijian, Suo, Chuanzhe, Liu, Yingtian, and Jin, Kefan
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- 2021
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19. A dual-arm mobile robot system performing assistive tasks operated via P300-based brain computer interface
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Gillini, Giuseppe, Di Lillo, Paolo, Arrichiello, Filippo, Di Vito, Daniele, Marino, Alessandro, Antonelli, Gianluca, and Chiaverini, Stefano
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- 2022
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20. Adaptive neural network-based path tracking control for autonomous combine harvester with input saturation
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Zhang, Yuexin, Wang, Lihui, and Liu, Yaodong
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- 2021
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21. 26.1: Invited Paper: Display Evaluation for Advanced Human‐Robot Interaction.
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Blankenbach, Karlheinz, Hochdorfer, Siegfried, Babel, Franziska, and Charrier, Etienne
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HUMAN-robot interaction ,PUBLIC spaces ,AUTONOMOUS robots ,LED displays ,INFORMATION display systems ,PEDESTRIANS - Abstract
Autonomous robots become increasingly widespread in public spaces. Human‐robot interactions (HRI) with pedestrians is essential by visualizing trajectory information. We evaluated various display technologies for bright indoor conditions such as animated projection and LED lighting as well as displays. [ABSTRACT FROM AUTHOR]
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- 2021
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22. Adaptive Whale Optimization Algorithm–DBiLSTM for Autonomous Underwater Vehicle (AUV) Trajectory Prediction.
- Author
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Guo, Shufang, Zhang, Jing, and Zhang, Tianchi
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AUTONOMOUS underwater vehicles ,ARTIFICIAL neural networks ,REMOTE submersibles ,AUTONOMOUS robots ,FORECASTING - Abstract
AUVs are autonomous underwater robots equipped with advanced sensors and navigation systems. Due to the complexity and uncertainty of the marine environment, AUVs are susceptible to the effects of the marine environment and may experience communication delays or even accidents. Based on the aforementioned issues, this paper proposes a prediction method for lost AUVs based on an adaptive optimization depth BiLSTM (AWOA-DBiLSTM) neural network model. To enhance prediction accuracy, AWOA-DBiLSTM employs a double BiLSTM to extract AUV features from positional information and physical attitude. Additionally, AWOA-DBiLSTM utilizes a gating mechanism to filter and reset physical attitude feature information to obtain features associated with positional information. After undergoing filtering operations, the physical attitude information of the AUV is fused with the position information to achieve trajectory prediction. For the first time, the differentiation and stratified extraction of AUV data features are presented in this paper. The experimental results demonstrate that the model achieves significant improvements in prediction accuracy and generalization, and the present study is of great significance for application in the task of predicting the trajectories of lost AUVs. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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23. Practical, Ethical, and Overlooked: Teleoperated Socially Assistive Robots in the Quest for Autonomy.
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Elbeleidy, Saad, Mott, Terran, and Williams, Tom
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AUTONOMOUS robots ,MOTIVATION (Psychology) ,CRITICAL thinking ,REMOTE control ,ROBOTS - Abstract
Socially Assistive Robots (SARs) show significant promise in a number of domains: providing support for the elderly, assisting in education, and aiding in therapy. Perhaps unsurprisingly, SAR research has traditionally focused on providing evidence for this potential. In this paper, we argue that this focus has led to a lack of critical reflection on the appropriate level of autonomy (LoA) for SARs, which has in turn led to blind spots in the research literature. Through an analysis of the past five years of HRI literature, we demonstrate that SAR researchers are overwhelmingly developing and envisioning autonomous robots. Critically, researchers do not include a rationale for their choice in LoA, making it difficult to determine their motivation for fully autonomous robots. We argue that defaulting to research fully autonomous robots is potentially short-sighted, as applying LoA selection guidelines to many SAR domains would seem to warrant levels of autonomy that are closer to teleoperation. We moreover argue that this is an especially critical oversight as teleoperated robots warrant different evaluation metrics than do autonomous robots since teleoperated robots introduce an additional user, the teleoperator. Taken together, this suggests a mismatch between LoA selection guidelines and the vision of SAR autonomy found in the literature. Based on this mismatch, we argue that the next five years of SAR research should be characterized by a shift in focus towards teleoperation and teleoperators. [ABSTRACT FROM AUTHOR]
- Published
- 2022
24. ARM4CH: A Methodology for Autonomous Reality Modelling for Cultural Heritage.
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Giakoumidis, Nikolaos and Anagnostopoulos, Christos-Nikolaos
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HISTORIC sites ,DIGITAL twins ,CULTURAL property ,AUTONOMOUS robots ,SCIENTIFIC community - Abstract
Nowadays, the use of advanced sensors, such as terrestrial, mobile 3D scanners and photogrammetric imaging, has become the prevalent practice for 3D Reality Modeling (RM) and the digitization of large-scale monuments of Cultural Heritage (CH). In practice, this process is heavily related to the expertise of the surveying team handling the laborious planning and time-consuming execution of the 3D scanning process tailored to each site's specific requirements and constraints. To minimize human intervention, this paper proposes a novel methodology for autonomous 3D Reality Modeling of CH monuments by employing autonomous robotic agents equipped with the appropriate sensors. These autonomous robotic agents are able to carry out the 3D RM process in a systematic, repeatable, and accurate approach. The outcomes of this automated process may also find applications in digital twin platforms, facilitating secure monitoring and the management of cultural heritage sites and spaces, in both indoor and outdoor environments. The main purpose of this paper is the initial release of an Industry 4.0-based methodology for reality modeling and the survey of cultural spaces in the scientific community, which will be evaluated in real-life scenarios in future research. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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25. Application of Autonomous Mobile Robot as a Substitute for Human Factor in Order to Increase Efficiency and Safety in a Company.
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Kubasáková, Iveta, Kubáňová, Jaroslava, Benčo, Dominik, and Fábryová, Nikola
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AUTONOMOUS robots ,MOBILE robots ,INDUSTRIAL efficiency ,MOBILE apps ,MATERIALS handling equipment ,ROBOTIC exoskeletons - Abstract
In this paper, we will compare two solution options to determine whether the deployment of an autonomous mobile robot will be a beneficial investment for a company not only in terms of cost, time, and manpower savings, but also in terms of efficiency and reliability in the implementation of selected logistics processes to ensure the smooth running of production. In this paper, we would like to analyse the technology in terms of functions, carrying capacity, and interconnection within the infrastructure in the enterprise. The logistics processes from material order to export to the final customer will be analysed when an automatically controlled robot is deployed. One of the solutions discusses the use of personnel and material handling equipment (tractor with transport kit). The second solution discusses the deployment of the robot and selected logistics processes. The paper concludes with a summary of both options in terms of time, cost, and efficiency of the solution. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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26. High-Precision BEV-Based Road Recognition Method for Warehouse AMR Based on IndoorPathNet and Transfer Learning.
- Author
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Zhang, Tianwei, He, Ci, Li, Shiwen, Lai, Rong, Wang, Zili, Qiu, Lemiao, and Zhang, Shuyou
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WAREHOUSES ,AUTONOMOUS robots ,MOBILE robots ,INDUSTRY 4.0 ,WAREHOUSING & storage ,NAVIGATION ,MOBILE apps - Abstract
Featured Application: An autonomous mobile robot (AMR) is a self-navigating vehicle capable of executing specific tasks such as transportation and cruising. As a crucial component of the logistics system in Industry 4.0 and smart factories, AMRs leverage sensors, including cameras, to gather information about their external environment and chart navigational paths. Their applications are diverse, spanning across warehousing, manufacturing, healthcare, hazardous locations, and specialized industries. Road recognition, a key feature of AMRs, employs technologies like semantic segmentation to extract high-level scene information, including object locations and semantic data from images. This technology can be integrated with Visual Simultaneous Localization and Mapping (SLAM), enhancing the AMR's ability to navigate complex environments. This integration is pivotal in enabling AMRs to successfully complete their navigation tasks. The rapid development and application of AMRs is important for Industry 4.0 and smart logistics. For large-scale dynamic flat warehouses, vision-based road recognition amidst complex obstacles is paramount for improving navigation efficiency and flexibility, while avoiding frequent manual settings. However, current mainstream road recognition methods face significant challenges of unsatisfactory accuracy and efficiency, as well as the lack of a large-scale high-quality dataset. To address this, this paper introduces IndoorPathNet, a transfer-learning-based Bird's Eye View (BEV) indoor path segmentation network that furnishes directional guidance to AMRs through real-time segmented indoor pathway maps. IndoorPathNet employs a lightweight U-shaped architecture integrated with spatial self-attention mechanisms to augment the speed and accuracy of indoor pathway segmentation. Moreover, it surmounts the challenge of training posed by the scarcity of publicly available semantic datasets for warehouses through the strategic employment of transfer learning. Comparative experiments conducted between IndoorPathNet and four other lightweight models on the Urban Aerial Vehicle Image Dataset (UAVID) yielded a maximum Intersection Over Union (IOU) of 82.2%. On the Warehouse Indoor Path Dataset, the maximum IOU attained was 98.4% while achieving a processing speed of 9.81 frames per second (FPS) with a 1024 × 1024 input on a single 3060 GPU. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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27. Localized Path Planning for Mobile Robots Based on a Subarea-Artificial Potential Field Model.
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Lv, Qiang, Hao, Guoqiang, Huang, Zhen, Li, Bin, Fu, Dandan, Zhao, Huanlong, Chen, Wei, and Chen, Sheng
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ROBOTIC path planning ,MOBILE robots ,TRAVEL time (Traffic engineering) ,AUTONOMOUS robots ,ENERGY consumption ,LOCALIZATION (Mathematics) - Abstract
The artificial potential field method has efficient obstacle avoidance ability, but this traditional method suffers from local minima, unreasonable paths, and sudden changes in heading angles during obstacle avoidance, leading to rough paths and increased energy consumption. To enable autonomous mobile robots (AMR) to escape from local minimum traps and move along reasonable, smooth paths while reducing travel time and energy consumption, in this paper, an artificial potential field method based on subareas is proposed. First, the optimal virtual subgoal was obtained around the obstacles based on the relationship between the AMR, obstacles, and goal points in the local environment. This was done according to the virtual subgoal benefit function to solve the local minima problem and select a reasonable path. Secondly, when AMR encountered an obstacle, the subarea-potential field model was utilized to solve problems such as path zigzagging and increased energy consumption due to excessive changes in the turning angle; this helped to smooth its planning path. Through simulations and actual testing, the algorithm in this paper demonstrated smoother heading angle changes, reduced energy consumption, and a 10.95% average reduction in movement time when facing a complex environment. This proves the feasibility of the algorithm. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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28. HoloSLAM: a novel approach to virtual landmark-based SLAM for indoor environments.
- Author
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Lahemer, Elfituri S. and Rad, Ahmad
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AUTONOMOUS robots ,VIRTUAL reality ,HUMANOID robots ,EXPLICIT instruction ,MOBILE robots ,ROBOTICS - Abstract
In this paper, we present HoloSLAM which is a novel solution to landmark detection issues in the simultaneous localization and mapping (SLAM) problem in autonomous robot navigation. The approach integrates real and virtual worlds to create a novel mapping robotic environment employing a mixed-reality technique and a sensor, namely Microsoft HoloLens. The proposed methodology allows the robot to interact and communicate with its new environment in real-time and overcome the limitations of conventional landmark-based SLAMs by creating and placing some virtual landmarks in situations where real landmarks are scarce, non-existent, or hard to be detected. The proposed approach enhances the robot's perception and navigation capabilities in various robot environments. The overall process contributes to the robot's more accurate understanding of its environment; thus, enabling it to navigate with greater efficiency and effectiveness. In addition, the newly implemented HoloSLAM offers the option to guide the robot to a specific location eliminating the need for explicit navigation instructions. The open-source framework proposed in this paper can benefit the robotics community by providing a more reliable, realistic, and robust mapping solution. The experiments show that the Ellipsoidal-HoloSLAM system is accurate and effectively overcomes the limitations of conventional Ellipsoidal-SLAMs, providing a more precise and detailed mapping of the robot's environment. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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29. Anomaly Detection Methods in Autonomous Robotic Missions.
- Author
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Chirayil Nandakumar, Shivoh, Mitchell, Daniel, Erden, Mustafa Suphi, Flynn, David, and Lim, Theodore
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INTRUSION detection systems (Computer security) ,ROBOTICS ,AUTONOMOUS robots ,RESEARCH & development - Abstract
Since 2015, there has been an increase in articles on anomaly detection in robotic systems, reflecting its growing importance in improving the robustness and reliability of the increasingly utilized autonomous robots. This review paper investigates the literature on the detection of anomalies in Autonomous Robotic Missions (ARMs). It reveals different perspectives on anomaly and juxtaposition to fault detection. To reach a consensus, we infer a unified understanding of anomalies that encapsulate their various characteristics observed in ARMs and propose a classification of anomalies in terms of spatial, temporal, and spatiotemporal elements based on their fundamental features. Further, the paper discusses the implications of the proposed unified understanding and classification in ARMs and provides future directions. We envisage a study surrounding the specific use of the term anomaly, and methods for their detection could contribute to and accelerate the research and development of a universal anomaly detection system for ARMs. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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30. An Audio-Based SLAM for Indoor Environments: A Robotic Mixed Reality Presentation.
- Author
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Lahemer, Elfituri S. F. and Rad, Ahmad
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MIXED reality ,MICROPHONES ,ROBOTICS ,MICROPHONE arrays ,AUTONOMOUS robots ,HUMANOID robots ,ROBOTS - Abstract
In this paper, we present a novel approach referred to as the audio-based virtual landmark-based HoloSLAM. This innovative method leverages a single sound source and microphone arrays to estimate the voice-printed speaker's direction. The system allows an autonomous robot equipped with a single microphone array to navigate within indoor environments, interact with specific sound sources, and simultaneously determine its own location while mapping the environment. The proposed method does not require multiple audio sources in the environment nor sensor fusion to extract pertinent information and make accurate sound source estimations. Furthermore, the approach incorporates Robotic Mixed Reality using Microsoft HoloLens to superimpose landmarks, effectively mitigating the audio landmark-related issues of conventional audio-based landmark SLAM, particularly in situations where audio landmarks cannot be discerned, are limited in number, or are completely missing. The paper also evaluates an active speaker detection method, demonstrating its ability to achieve high accuracy in scenarios where audio data are the sole input. Real-time experiments validate the effectiveness of this method, emphasizing its precision and comprehensive mapping capabilities. The results of these experiments showcase the accuracy and efficiency of the proposed system, surpassing the constraints associated with traditional audio-based SLAM techniques, ultimately leading to a more detailed and precise mapping of the robot's surroundings. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
31. Online Calibration of Extrinsic Parameters for Solid-State LIDAR Systems.
- Author
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Mints, Mark O., Abayev, Roman, Theisen, Nick, Paulus, Dietrich, and von Gladiss, Anselm
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MEAN square algorithms ,LIDAR ,STANDARD deviations ,CALIBRATION ,FEATURE extraction ,AUTONOMOUS robots ,SOLID-state lasers - Abstract
This work addresses the challenge of calibrating multiple solid-state LIDAR systems. The study focuses on three different solid-state LIDAR sensors that implement different hardware designs, leading to distinct scanning patterns for each system. Consequently, detecting corresponding points between the point clouds generated by these LIDAR systems—as required for calibration—is a complex task. To overcome this challenge, this paper proposes a method that involves several steps. First, the measurement data are preprocessed to enhance its quality. Next, features are extracted from the acquired point clouds using the Fast Point Feature Histogram method, which categorizes important characteristics of the data. Finally, the extrinsic parameters are computed using the Fast Global Registration technique. The best set of parameters for the pipeline and the calibration success are evaluated using the normalized root mean square error. In a static real-world indoor scenario, a minimum root mean square error of 7 c m was achieved. Importantly, the paper demonstrates that the presented approach is suitable for online use, indicating its potential for real-time applications. By effectively calibrating the solid-state LIDAR systems and establishing point correspondences, this research contributes to the advancement of multi-LIDAR fusion and facilitates accurate perception and mapping in various fields such as autonomous driving, robotics, and environmental monitoring. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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- View/download PDF
32. A Performance Comparison between Different Industrial Real-Time Indoor Localization Systems for Mobile Platforms.
- Author
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Rebelo, Paulo M., Lima, José, Soares, Salviano Pinto, Moura Oliveira, Paulo, Sobreira, Héber, and Costa, Pedro
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AUTONOMOUS robots ,MOBILE robots ,FLIGHT simulators ,FORKLIFT trucks ,MOBILE operating systems - Abstract
The flexibility and versatility associated with autonomous mobile robots (AMR) have facilitated their integration into different types of industries and tasks. However, as the main objective of their implementation on the factory floor is to optimize processes and, consequently, the time associated with them, it is necessary to take into account the environment and congestion to which they are subjected. Localization, on the shop floor and in real time, is an important requirement to optimize the AMRs' trajectory management, thus avoiding livelocks and deadlocks during their movements in partnership with manual forklift operators and logistic trains. Threeof the most commonly used localization techniques in indoor environments (time of flight, angle of arrival, and time difference of arrival), as well as two of the most commonly used indoor localization methods in the industry (ultra-wideband, and ultrasound), are presented and compared in this paper. Furthermore, it identifies and compares three industrial indoor localization solutions: Qorvo, Eliko Kio, and Marvelmind, implemented in an industrial mobile platform, which is the main contribution of this paper. These solutions can be applied to both AMRs and other mobile platforms, such as forklifts and logistic trains. In terms of results, the Marvelmind system, which uses an ultrasound method, was the best solution. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
33. Research on the Relative Position Detection Method between Orchard Robots and Fruit Tree Rows.
- Author
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Gu, Baoxing, Liu, Qin, Gao, Yi, Tian, Guangzhao, Zhang, Baohua, Wang, Haiqing, and Li, He
- Subjects
FRUIT trees ,ORCHARDS ,TREE trunks ,AUTONOMOUS robots ,LEAST squares ,MOBILE robots - Abstract
The relative position of the orchard robot to the rows of fruit trees is an important parameter for achieving autonomous navigation. The current methods for estimating the position parameters between rows of orchard robots obtain low parameter accuracy. To address this problem, this paper proposes a machine vision-based method for detecting the relative position of orchard robots and fruit tree rows. First, the fruit tree trunk is identified based on the improved YOLOv4 model; second, the camera coordinates of the tree trunk are calculated using the principle of binocular camera triangulation, and the ground projection coordinates of the tree trunk are obtained through coordinate conversion; finally, the midpoints of the projection coordinates of different sides are combined, the navigation path is obtained by linear fitting with the least squares method, and the position parameters of the orchard robot are obtained through calculation. The experimental results show that the average accuracy and average recall rate of the improved YOLOv4 model for fruit tree trunk detection are 5.92% and 7.91% higher, respectively, than those of the original YOLOv4 model. The average errors of heading angle and lateral deviation estimates obtained based on the method in this paper are 0.57° and 0.02 m. The method can accurately calculate heading angle and lateral deviation values at different positions between rows and provide a reference for the autonomous visual navigation of orchard robots. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
34. Socially acceptable robot behavior: Approaches for learning, adaptation and evaluation.
- Author
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Roesler, Oliver, Bagheri, Elahe, Aly, Amir, Rossi, Silvia, and Alami, Rachid
- Subjects
AUTONOMOUS robots ,ROBOTS ,COGNITIVE robotics ,MOBILE robots ,FIVE-factor model of personality ,ARTIFICIAL intelligence ,HUMAN-robot interaction - Abstract
A key factor for the acceptance of robots as regular partners in human-centered environments is the appropriateness and predictability of their behavior. Another challenge is that not all human social norms are applicable for human-robot interactions, while there might also be norms that only exist for human-robot interactions. Exploring the Design Space of Robot Appearance and Behavior in an Attention-Seeking "Living Room" Scenario for a Robot Companion. [Extracted from the article]
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- 2023
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35. A Study on the Rapid Detection of Steering Markers in Orchard Management Robots Based on Improved YOLOv7.
- Author
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Gao, Yi, Tian, Guangzhao, Gu, Baoxing, Zhao, Jiawei, Liu, Qin, Qiu, Chang, and Xue, Jinlin
- Subjects
AUTONOMOUS robots ,ROBOTS ,ORCHARDS ,ORCHARD management ,FRUIT trees ,COMPUTER vision - Abstract
In order to guide the orchard management robot to realize autonomous steering in the row ends of a complex orchard environment, this paper proposes setting up steering markers in the form of fruit trees at the end of the orchard rows and realizing the rapid detection of the steering markers of the orchard management robot through the fast and accurate recognition and classification of different steering markers. First, a high-precision YOLOv7 model is used, and the depthwise separable convolution (DSC) is used instead of the 3 × 3 ordinary convolution, which improves the speed of model detection; at the same time, in order to avoid a decline in detection accuracy, the Convolutional Block Attention Module (CBAM) is added to the model, and the Focal loss function is introduced to improve the model's attention to the imbalanced samples. Second, a binocular camera is used to quickly detect the steering markers, obtain the position information of the robot to the steering markers, and determine the starting point position of the robot's autonomous steering based on the position information. Our experiments show that the average detection accuracy of the improved YOLOv7 model reaches 96.85%, the detection time of a single image reaches 15.47 ms, and the mean value of the localization error is 0.046 m. Comparing with the YOLOv4, YOLOv4-tiny, YOLOv5-s, and YOLOv7 models, the improved YOLOv7 model outperforms the other models in terms of combined detection time and detection accuracy. Therefore, the model proposed in this paper can quickly and accurately perform steering marker detection and steering start point localization, avoiding problems such as steering errors and untimely steering, shortening the working time and improving the working efficiency. This model also provides a reference and technical support for research on robot autonomous steering in other scenarios. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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36. Multi-Robot Task Scheduling for Consensus-Based Fault-Resilient Intelligent Behavior in Smart Factories.
- Author
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Kalempa, Vivian Cremer, Piardi, Luis, Limeira, Marcelo, and de Oliveira, Andre Schneider
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AUTONOMOUS robots ,INTELLIGENT buildings ,COLLECTIVE behavior ,FACTORIES ,OVERHEAD costs ,MOBILE robots ,WAREHOUSES - Abstract
In smart factories, several mobile and autonomous robots are being utilized in warehouses to reduce overhead and operating costs. In this context, this paper presents a consensus-based fault-resilient intelligent mechanism called Consensual Fault-Resilient Behavior (CFRB). The proposed approach is based on three hierarchical plans: imposition, negotiation, and consensus. Fault resilience is achieved using the collective behavior of a multi-robot system that applies ternary decisions based on these plans. The difference between this paper and our previous work is on the consensual level. As it is suitable for the analysis and design of coordinated behavior between autonomous robots, the consensus plan is restructured and enhanced. The proposed approach is tested and evaluated in a virtual warehouse based on a real environment. In addition, it is compared with other current approaches, and the results are presented, demonstrating its efficiency. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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37. DEVELOPMENT AND TESTING OF AUTOMATED CONTROL SYSTEM FOR SEA BUCKTHORN BERRY HARVESTING ROBOT “AGROBOT”.
- Author
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Stupans, Andrejs, Maksimkins, Pavels, Senfelds, Armands, and Ribickis, Leonids
- Subjects
- *
AUTOMATIC control systems , *SEA buckthorn , *BERRY harvesting , *AGRICULTURAL technology , *AUTONOMOUS robots - Abstract
The paper describes the control system of an autonomous agriculture robot and evaluates its operation using a laboratory stand and a digital environment. AgroBot is an autonomous sea buckthorn berry harvesting robot. It automatically finds the bush branches to harvest, cuts them, and stores them in a box. AgroBot consists of a 3 DOF (Degrees of Freedom) Cartesian mobile platform and a Hyundai HH7 industrial robot arm with 6 DOF. The control system is specifically designed for real-time operation, enabling AgroBot to adapt to dynamic environmental conditions (wind, varying light) that complicate target tracking. The control system consists of two modules operating as two separate programs. The first module is the Computer Vision Module (CVM) which has high-level control of AgroBot operation. It uses feed from cameras to find the cutting spot and sends commands to approach, cut, store, and search. The module is written in Python. The second module is the Robot Control Module (RCM) which receives high-level commands from CVM and manages lower-level control of the Hyundai Controller (HC). RCM calculates the robot trajectory to a target position, communicates with both CVM and HC in parallel threads and handles errors. As HC requires time-critical control, RCM is written in C + + . RCM and CVM are running on one computer communicating via sockets. As the mobile platform hardware is in the development stage and is not available at the moment, the digital twin of the robot is created to test the system’s performance in a simulated environment. The input to the digital twin is the same as for the actual robot. It is the x, y, z position and orientation A, B, C using Euler angles. The digital twin visualization is developed in the Unity game engine. Matlab Robotic Toolbox is used with the Levenberg-Marquardt solver algorithm to calculate inverse kinematics of 9 DOF robot. The paper focuses on the Robot Control Module architecture and control system’s testing. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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38. Towards Contactless Learning Activities during Pandemics Using Autonomous Service Robots.
- Author
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Al Tarabsheh, Anas, Yaghi, Maha, Younis, AbdulRehman, Sarker, Razib, Moussa, Sherif, Eldigair, Yazeed, Hajjdiab, Hassan, El-Baz, Ayman, and Ghazal, Mohammed
- Subjects
AUTONOMOUS robots ,ARTIFICIAL intelligence ,COVID-19 pandemic ,PANDEMICS ,SCANNING systems ,HUMAN-robot interaction - Abstract
The COVID-19 pandemic has had a significant impact worldwide, impacting schools, undergraduate, and graduate university education. More than half a million lives have been lost due to COVID-19. Moving towards contactless learning activities has become a research area due to the rapid advancement of technology, particularly in artificial intelligence and robotics. This paper proposes an autonomous service robot for handling multiple teaching assistant duties in the educational field to move towards contactless learning activities during pandemics. We use SLAM to map and navigate the environment to proctor an exam. We also propose a human–robot voice interaction and an academic content personalization algorithm. Our results show that our robot can navigate the environment to proctor students avoiding any static or dynamic obstacles. Our cheating detection system obtained a testing accuracy of 86.85%. Our image-based exam paper scanning system can scan, extract, and process exams with high accuracy. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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39. Mathematics in Robot Control for Theoretical and Applied Problems.
- Author
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Mercorelli, Paolo, Sergiyenko, Oleg, and Tsymbal, Oleksandr
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ROBOT control systems ,ROBOT design & construction ,ROBOT motion ,TRACKING control systems ,AUTONOMOUS robots ,MOBILE robots - Abstract
The article discusses the importance of mathematics in the field of robot control. It highlights the advancements in mathematical methods for solving theoretical and applied problems in various areas of robotics, such as solar tracking systems, robotic manipulators, computer vision, and navigation. The article presents a collection of research papers that demonstrate how mathematics can be used to solve complex problems and improve the practical use of robotic systems. The papers cover a wide range of topics, including adaptive control, logical paradigms, encryption, kinematic modeling, cooperative control, and autonomous navigation. Overall, the article emphasizes the central role of mathematics in advancing the field of robot control. [Extracted from the article]
- Published
- 2024
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40. Exploration of a Simple Navigation Method for Swarm Robots Pioneered by Heterogeneity.
- Author
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Sueoka, Yuichiro, Okada, Mitsuki, Tsunoda, Yusuke, Sugimoto, Yasuhiro, and Osuka, Koichi
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MOBILE robots ,INDUSTRIAL robots ,ROBOTS ,AUTONOMOUS robots ,ROBOT design & construction ,HETEROGENEITY - Abstract
In recent years, research has been conducted on swarm robot systems in which multiple autonomous mobile robots cooperate to perform tasks. Swarm robot systems are expected to perform high functionality as a group by cooperating with each other, in spite of the limited capabilities of the individual robots. This paper explores a method of simplifying swarm robot controllers as much as possible for swarm robot navigation. If we can achieve autonomous navigation of swarm robots to a target area with minimal resource consumption, they only need to implement the task execution function in that area. This leads to lower costs for swarm robot design and more efficient system architecture design. To address the above aims, this study focuses on heterogeneity. Specifically, we introduce a navigator robot that indirectly guides swarm robots named the worker robots. Heterogeneity in this paper refers to the worker robots and the navigator robots. We design the interaction between the navigator robot and the worker robots to provide a system that guides the worker robots to the destination. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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41. Research on Road Sign Detection and Visual Depth Perception Technology for Mobile Robots.
- Author
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Zhao, Jianwei and Liu, Yushuo
- Subjects
DEPTH perception ,VISUAL perception ,TRAFFIC signs & signals ,MOBILE robots ,AUTONOMOUS robots ,AUTOMATION - Abstract
To accomplish the task of detecting and avoiding road signs by mobile robots for autonomous running, in this paper, we propose a method of road sign detection and visual depth perception based on improved Yolov5 and improved centroid depth value filtering. First, the Yolov5 model has a large number of parameters, a large computational volume, and a large model size, which is difficult to deploy to the CPU side (industrial control computer) of the robot mobile platform. To solve this problem, the study proposes a lightweight Yolov5-SC3FB model. Compared with the original Yolov5n model, the Yolov5-SC3FB model only loses lower detection accuracy, the parameter volume is reduced to 0.19 M, the computational volume is reduced to 0.5 GFLOPS, and the model size is only 0.72 MB, making it easy to deploy on mobile robot platforms. Secondly, the obtained depth value of the center point of the bounding box is 0 due to the influence of noise. To solve this problem, we proposed an improved filtering method for the depth value of the center point in the study, and the relative error of its depth measurement is only 2%. Finally, the improved Yolov5-SC3FB model is fused with the improved filtering method for acquiring centroid depth values and the fused algorithm is deployed to the mobile robot platform. We verified the effectiveness of this fusion algorithm for the detection and avoidance of road signs of the robot. Thus, it can enable the mobile robot to correctly perceive the environment and achieve autonomous running. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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42. Robots and Autonomous Machines for Sustainable Agriculture Production.
- Author
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Yuan, Jin, Ji, Wei, and Feng, Qingchun
- Subjects
SUSTAINABLE agriculture ,SUSTAINABILITY ,AUTONOMOUS robots ,AGRICULTURAL technology ,AGRICULTURAL robots ,PRUNING ,PRECISION farming - Abstract
Vrchota et al. [[21]] evaluated precision agriculture technologies' practical use in agricultural enterprises in the Czech Republic, which is a reference for the development and implementation of precision agriculture technology and equipment in each country. The global agriculture faces critical pressures, including an aging population, rising production costs, and labor shortages. 10.3390/agriculture12071051 14 Liu L., Yuan J., Gong L., Wang X., Liu X. Dynamic Fresh Weight Prediction of Substrate-Cultivated Lettuce Grown in a Solar Greenhouse Based on Phenotypic and Environmental Data. For intelligent agricultural machines, Bai et al. [[1]] designed a monitoring system for the sowing quality of cotton precision planters, to realize the real-time monitoring of the cotton precision seeding operation processes and improve the intelligence level of cotton precision planters. [Extracted from the article]
- Published
- 2023
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43. Defense Management Science on Artificial Intelligence and Autonomous Robot.
- Author
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SOEBANDRIJA, Khristian Edi Nugroho
- Subjects
DEFENSE industries ,AUTONOMOUS robots ,ARTIFICIAL intelligence ,INDUSTRIAL robots ,QUANTITATIVE research - Abstract
Defense management science has been evolving from its original form of the defense mechanism. To some extent, defense management science, in brief form of defense mechanisms of military, police and civilian, has been developing from time to time. The development refers to the transformation from the full involvement of humans, into the less involvement of humans, as it was replaced by technology. This paper focuses on the mentioned technology within the scope of artificial intelligence and autonomous robots. Despite the wide range of defense mechanisms within military, police and civilian; this paper elaborates the major parts of defense mechanism, known as defense management science in military perspective. To be precise, the defense management science in this paper furthermore explores the benefit of drones through their artificial intelligence in winning the battles and ultimately its war. The purpose of this paper is to elaborate on the wide variety of combinations of defense management science using both artificial intelligence and autonomous robots to win battles and ultimately war. The research methodology in this paper emphasizes the quantitative approaches. Yet, it opens to the options on using qualitative method as well. [ABSTRACT FROM AUTHOR]
- Published
- 2023
44. Navigation Path Following Platform for a Greenhouse Shuttle Robot Using the State-flow Method.
- Author
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Yoo, Heonjong, Baek, Donkyu, and Choi, Seong-gon
- Subjects
MOBILE robots ,SHUTTLE services ,NETWORK operating system ,ANGULAR velocity ,GLOBAL Positioning System ,ROBOT control systems ,AUTONOMOUS robots - Abstract
Localization is an important method for autonomous indoor robots to recognize their positions. Generally, the navigation of a mobile robot is conducted using a camera, Lidar, and global positioning system. However, for an indoor environment, GPS is unavailable. Therefore, a, state-trajectory tracking method is utilized based on a Lidar map. This paper presents the path following of an autonomous indoor mobile robot, that is, a shuttle robot, using a state-flow method via a robot operating system network. MATLAB and Linux high-level computers and an inertial measurement unit sensor are used to obtain the Cartesian coordinate information of a bicycle-type mobile robot. The path following problem can be solved in the state-flow block by setting appropriate time and linear and angular velocity variables. After the predetermined time, the linear and angular velocities are set based on the length of the path and radius of the quarter-circle of the left and right turns in the state-flow block, path planning, which can execute the work effectively, is established using the state-flow algorithm. The state-flow block produces time-series data that are sent to Linux system, which facilitates real-time mobile platform path following scenario. Several cases within the path-following problem of the mobile robot were considered, depending on the linear and angular velocity settings: the mobile robot moved forward and backward, turned in the right and left directions on the circular path. The effectiveness of the method was demonstrated using the desktop-based indoor mobile robot control results. Thus, the paper focuses on the application of the state-flow algorithm to the shuttle robot specifically in the narrow indoor environment. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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45. A Review of Sensing Technologies for Indoor Autonomous Mobile Robots.
- Author
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Liu, Yu, Wang, Shuting, Xie, Yuanlong, Xiong, Tifan, and Wu, Mingyuan
- Subjects
AUTONOMOUS robots ,MOBILE robots ,MULTISENSOR data fusion ,ROBOT industry ,INFORMATION measurement ,DATA mining - Abstract
As a fundamental issue in robotics academia and industry, indoor autonomous mobile robots (AMRs) have been extensively studied. For AMRs, it is crucial to obtain information about their working environment and themselves, which can be realized through sensors and the extraction of corresponding information from the measurements of these sensors. The application of sensing technologies can enable mobile robots to perform localization, mapping, target or obstacle recognition, and motion tasks, etc. This paper reviews sensing technologies for autonomous mobile robots in indoor scenes. The benefits and potential problems of using a single sensor in application are analyzed and compared, and the basic principles and popular algorithms used in processing these sensor data are introduced. In addition, some mainstream technologies of multi-sensor fusion are introduced. Finally, this paper discusses the future development trends in the sensing technology for autonomous mobile robots in indoor scenes, as well as the challenges in the practical application environments. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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- View/download PDF
46. Vehicle Trajectory Reconstruction Using Lagrange-Interpolation-Based Framework.
- Author
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Wang, Jizhao, Liang, Yunyi, Tang, Jinjun, and Wu, Zhizhou
- Subjects
STANDARD deviations ,KALMAN filtering ,PEARSON correlation (Statistics) ,WAVELET transforms ,AUTONOMOUS robots ,AUTONOMOUS vehicles - Abstract
Featured Application: This research contributes to the development of a technological method to obtain highly accurate vehicle trajectory data. The reconstructed trajectory data play a key role in traffic state prediction, traffic management and the decision making of autonomous vehicles and robots. Vehicle trajectory usually suffers from a large number of outliers and observation noises. This paper proposes a novel framework for reconstructing vehicle trajectories. The framework integrates the wavelet transform, Lagrange interpolation and Kalman filtering. The wavelet transform based on waveform decomposition in the time and frequency domain is used to identify the abnormal frequency of a trajectory. Lagrange interpolation is used to estimate the value of data points after outliers are removed. This framework improves computation efficiency in data segmentation. The Kalman filter uses normal and predicted data to obtain reasonable results, and the algorithm makes an optimal estimation that has a better denoising effect. The proposed framework is compared with a baseline framework on the trajectory data in the NGSIM dataset. The experimental results showed that the proposed framework can achieve a 45.76% lower root mean square error, 26.43% higher signal-to-noise ratio and 25.58% higher Pearson correlation coefficient. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
47. Tour guide robot: a 5G-enabled robot museum guide.
- Author
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Rosa, Stefano, Randazzo, Marco, Landini, Ettore, Bernagozzi, Stefano, Sacco, Giancarlo, Piccinino, Mara, Natale, Lorenzo, Bellas, Francisco, and Wu, Yan
- Subjects
TOUR guides (Persons) ,ROBOTS ,5G networks ,AUTONOMOUS robots ,MUSEUMS ,ROBOTICS - Abstract
This paper presents and discusses the development and deployment of a tour guide robot as part of the 5 g-TOURS EU research project, aimed at developing applications enabled by 5G technology in different use cases. The objective is the development of an autonomous robotic application where intelligence is off-loaded to a remote machine via 5G network, so as to lift most of the computational load from the robot itself. The application uses components that have been widely studied in robotics, (i.e., localization, mapping, planning, interaction). However, the characteristics of the network and interactions with visitors in the wild introduce specific problems which must be taken into account. The paper discusses in detail such problems, summarizing the main results achieved both from the methodologicaland the experimental standpoint, and is completed by the description of the general functional architecture of the whole system, including navigation and operational services. The software implementation is also publicly available. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
48. Path Following for Autonomous Mobile Robots with Deep Reinforcement Learning.
- Author
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Cao, Yu, Ni, Kan, Kawaguchi, Takahiro, and Hashimoto, Seiji
- Subjects
DEEP reinforcement learning ,REINFORCEMENT learning ,MOBILE learning ,MOBILE robots ,AUTONOMOUS robots ,NONHOLONOMIC constraints - Abstract
Autonomous mobile robots have become integral to daily life, providing crucial services across diverse domains. This paper focuses on path following, a fundamental technology and critical element in achieving autonomous mobility. Existing methods predominantly address tracking through steering control, neglecting velocity control or relying on path-specific reference velocities, thereby constraining their generality. In this paper, we propose a novel approach that integrates the conventional pure pursuit algorithm with deep reinforcement learning for a nonholonomic mobile robot. Our methodology employs pure pursuit for steering control and utilizes the soft actor-critic algorithm to train a velocity control strategy within randomly generated path environments. Through simulation and experimental validation, our approach exhibits notable advancements in path convergence and adaptive velocity adjustments to accommodate paths with varying curvatures. Furthermore, this method holds the potential for broader applicability to vehicles adhering to nonholonomic constraints beyond the specific model examined in this paper. In summary, our study contributes to the progression of autonomous mobility by harmonizing conventional algorithms with cutting-edge deep reinforcement learning techniques, enhancing the robustness of path following. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
49. MirrorVision: Light-Weight Floor Detection System for an Autonomous Robot in a Crowded Elevator.
- Author
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Khudoyberdiev, Azimbek and Jihoon Ryoo
- Subjects
AUTONOMOUS robots ,LOCAL delivery services ,FLOOR design & construction ,CONVOLUTIONAL neural networks ,COMMUNICATION barriers - Abstract
Delivering robots impact many facets of our life, including food delivery and restaurant services, with advancements enabling obstacle overcome, faster delivery, and minimizing human intervention. However, delivering robots remained to experience poor vertical mobilityelevator usage in multi-floor buildings. Incorporating new elevator models into the robot's elevator usage capabilities involves a long process of manufacturer approval and authentication. Furthermore, strict fire-code regulations pose communication barriers between the robot and the elevator. In this paper, we introduce MirrorVision-a novel approach designed for accurate floor detection during vertical mobility, regardless of obstructions blocking the robot's direct line of sight to the elevator number panel. First, we collected and pre-processed a dataset of direct and reflective views of elevator number panels via the preinstalled mirrors. Then, we trained mirrored images in various possibilities to accomplish accurate floor detection. MirrorVision provides a solid mechanism to understand floor numbers at the level of distorted images. Extensive evaluations show that MirrorVision achieves 98.8% accuracy for floor detection in a crowded elevator, while state-of-the-art EfficientDet and YOLOv5 achieved 90.8% and 93.3%, respectively. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
50. Self-Learning Robot Autonomous Navigation with Deep Reinforcement Learning Techniques.
- Author
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Pintos Gómez de las Heras, Borja, Martínez-Tomás, Rafael, and Cuadra Troncoso, José Manuel
- Subjects
DEEP reinforcement learning ,AUTONOMOUS robots ,MACHINE learning ,AUTODIDACTICISM ,REINFORCEMENT learning ,REWARD (Psychology) - Abstract
Complex and high-computational-cost algorithms are usually the state-of-the-art solution for autonomous driving cases in which non-holonomic robots must be controlled in scenarios with spatial restrictions and interaction with dynamic obstacles while fulfilling at all times safety, comfort, and legal requirements. These highly complex software solutions must cover the high variability of use cases that might appear in traffic conditions, especially when involving scenarios with dynamic obstacles. Reinforcement learning algorithms are seen as a powerful tool in autonomous driving scenarios since the complexity of the algorithm is automatically learned by trial and error with the help of simple reward functions. This paper proposes a methodology to properly define simple reward functions and come up automatically with a complex and successful autonomous driving policy. The proposed methodology has no motion planning module so that the computational power can be limited like in the reactive robotic paradigm. Reactions are learned based on the maximization of the cumulative reward obtained during the learning process. Since the motion is based on the cumulative reward, the proposed algorithm is not bound to any embedded model of the robot and is not being affected by uncertainties of these models or estimators, making it possible to generate trajectories with the consideration of non-holonomic constrains. This paper explains the proposed methodology and discusses the setup of experiments and the results for the validation of the methodology in scenarios with dynamic obstacles. A comparison between the reinforcement learning algorithm and state-of-the-art approaches is also carried out to highlight how the methodology proposed outperforms state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
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