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This paper proposes a novel modular selfreconfigurable robot (MSRR) "FreeBOT", which can be connected freely at any point on other robots. FreeBOT is mainly composed of two parts: a spherical ferromagnetic shell and an internal magnet. The connection between the modules is genderless and instant, since the internal magnet can freely attract other FreeBOT spherical ferromagnetic shells, and not need to be precisely aligned with the specified connector. This connection method has fewer physical constraints, so the FreeBOT system can be extended to more configurations to meet more functional requirements. FreeBOT can accomplish multiple tasks although it only has two motors: module independent movement, connector management and system reconfiguration. FreeBOT can move independently on the plane, and even climb on ferromagnetic walls; a group of FreeBOTs can traverse complex terrain. Numerous experiments have been conducted to test its function, which shows that the FreeBOT system has great potential to realize a freeform robotic system.

This paper introduces an obstacle-crossing strategy, and the self-reconfiguration algorithm for a new class of modular robots called the rolling sphere, which can fit obstacles represented by cubes of different sizes due to the chain connection of multiple spheres. For the self-reconfiguration of the rolling spheres, a large gradient is obtained by classifying its action types and hierarchically minimizing the distance between the initial configuration and the final configuration. The most direct use of this large gradient is the fast crossing of various obstacles, by jointing multiple self-reconfigurations according to the OctoMap of the obstacles. It is verified in simulation that the self-reconfiguration takes full advantage of the parallel movement of multiple modules to reduce the total time steps, and the obstacle-crossing strategy can adapt to a variety of obstacles.

Towards long range and high endurance sailing, energy is of utmost importance. Moreover, benefiting from the dominance of the sailboat itself, it is energy-saving and environment-friendly. Thus, the sailboat with energy planning problem is meaningful. However, until now, the sailboat energy optimization problem has rarely been considered. In this paper, we focus on the energy consumption optimization of an autonomous sailboat. It has been formulated as a Nonlinear Programming problem (NLP). We deal with it with a hybrid control scheme, in which pseudo-spectral (PS) optimal control method is used in heading control, and a model-free framework guided by Extreme Seeking Control (ESC) is used in sail control. The optimal path is generated with the optimal input motor torques in time series. As a result, both simulation and experiments have validated motion planning and energy planning performance. Notably, about 7% of energy is saved on average. Our proposed method can make sailboats sailing longer and sustainable.

Automatic latching for charging in a disturbed environment for Unmanned Surface Vehicle (USVs) is always a challenging problem. In this paper, we propose a two-stage automatic latching system for USVs charging in berth. In Stage I, a vision-guided algorithm is developed to calculate an optimal latching position for charging. In Stage II, a novel latching mechanism is designed to compensate the movement misalignments from the water disturbance. A set of experiments have been conducted in real-world environments. The results show the latching success rate has been improved from 40% to 73.3% in the best cases with our proposed system. Furthermore, the vision-guided algorithm provides a methodology to optimize the design radius of the latching mechanism with respect to different disturbance levels accordingly. Outdoor experiments have validated the efficiency of our proposed automatic latching system. The proposed system improves the autonomy intelligence of the USVs and provides great benefits for practical applications.

The coronavirus disease 2019 (COVID-19) outbreak has increased mortality and morbidity world-wide. Oropharyngeal swabbing is a well-known and commonly used sampling technique for COVID-19 diagnose around the world. We developed a robot to assist with COVID-19 oropharyngeal swabbing to prevent frontline clinical staff from being infected. The robot integrates a UR5 manipulator, rigid-flexible coupling (RFC) manipulator, force-sensing and control subsystem, visual subsystem and haptic device. The robot has strength in intrinsically safe and high repeat positioning accuracy. In addition, we also achieve one-dimensional constant force control in the automatic scheme (AS). Compared with the rigid sampling robot, the developed robot can perform the oropharyngeal swabbing procedure more safely and gently, reducing risk. Alternatively, a novel robot control schemes called collaborative manipulation scheme (CMS) which combines a automatic phase and teleoperation phase is proposed. At last, comparative experiments of three schemes were conducted, including CMS, AS, and teleoperation scheme (TS). The experimental results shows that CMS obtained the highest score according to the evaluation equation. CMS has the excellent performance in quality, experience and adaption. Therefore, the proposal of CMS is meaningful which is more suitable for robot-sampling.

This paper presents a novel Cable Climbing Robot CCRobot-III, which is the third version designed for bridge cable inspection tasks, aiming at surpassing previous versions in terms of climbing speed and payload capacity. Benefiting from Split-type Wire-driven design, CCRobot-III can climb along a 90-110mm diameter bridge cable in inchworm-like gait at a speed of up to 12m/min, and carrying more than 40kg payload at the same time. CCRobot-III consists of a climbing precursor and a main-body frame. The two parts are connected and driven by steel wires. The climbing precursor, acting as a mobile anchor, moves quickly on a bridge cable. The mainbody frame, acting as a mobile winch, carries payload and pulls itself to a certain position with steel wires. Both parts have one or two pairs of palm-based gripper, which is the key component for providing strong adhesion to support the robot climbing. Experimental results have shown that CCRobotIII possesses outstanding climbing performance, high payload capacity, and good adaptability to complex conditions of cable surface. Moreover, it has potential engineering applications on the cable-stayed bridge for fieldwork.

Traditional solar trackers often adopt motors to automatically adjust the attitude of the solar panels towards the sun for maximum power efficiency. In this paper, a novel design of solar tracker for the ocean environment is introduced. Utilizing the fluctuations due to the waves, electromagnetic brakes are utilized instead of motors to adjust the attitude of the solar panels. Compared with the traditional solar trackers, the proposed one is simpler in hardware while the harvesting efficiency is similar. The desired attitude is calculated out of the local location and time. Then based on the dynamic model of the system, the angular acceleration of the solar panels is estimated and a control algorithm is proposed to decide the release and lock states of the brakes. In such a manner, the adjustment of the attitude of the solar panels can be achieved by using two brakes only. Experiments are conducted to validate the acceleration estimator and the dynamic model. At last, the feasibility of the proposed solar tracker is tested on the real water surface. The results show that the system is able to adjust 40° in two dimensions within 28 seconds.

Collaborative object transportation has become a popular study trend with its remarkable application foreground. In previous relevant studies, localization of the transported object has always been accomplished by additional devices rather than robot onboard equipments. This paper presents a generalized multi-robot leader-follower system for collaborative object transportation and an onboard object localization algorithm for trajectory tracking of the target object. In this system, the mobile robots can directly push a cubic object without extra gripping devices, when tracking the reference trajectory. During the control process, the object is regarded as an virtual leader, whose localization information is utilized as the feedback, while the mobile robots are considered as the followers. In absence of external localization systems, the proposed onboard localization algorithm provides the real-time position information of the object using scan data from lidars equipped on the robots. A performed measurement accuracy test shows high precision of this algorithm. Finally, a lane-changing experiment of object transportation is conducted, and it verifies this multi-robot leader-follower system.

Wind-driven vehicle is a kind of promising way to utilize wind energy due to its non-pollution feature. This paper presents a practical design of the wind-driven vehicle in the form of land-yacht, which is equipped with a wing sail and a micro-controller unit. Theoretical analysis and simulation were performed to find the total force coefficient corresponding to each combination of attack angle and heading angle, and the best attack angle corresponding to each different heading angle. A prototype was built and tested in a wind-field environment. The simulation and experiment were concordant, both of which showed the relation between the movement of land-yacht and these angles when moving upwind well.

Obstacle avoidance of autonomous sailboats is a complicated task due to big inertia, highly nonlinear motion of sailboat and uncertain disturbance from wind and water current. To deal with the obstacle avoidance problem of autonomous sailboats, we promote a novel method based on reinforcement learning with coarse-to-fine strategy. In this strategy, coarse stage is used to detect the autonomous sailboat roughly in the test environment. Then fine stage is applied to localize the autonomous sailboat accurately. Hereby, the avoidance performance is improved by the transition from coarse to fine. We have verified our algorithms both in simulation and real experiments. With our method, the sailboat avoids the obstacle in higher precision than the method without the coarse-to-fine strategy. The final success rate of obstacle avoidance is near 83% and the rate of reaching goal is 70%. Both simulation results and experiments show that our method is effective.

The commercial solar energy market is dominated by non-concentrating photovoltaics and concentrating solar thermal systems. With the development of high efficiency thermoelectric materials, the solar thermoelectric generator is becoming to be a competitive alternative solar energy technology in certain applications. This paper proposes a simulation model and a design methodology for solar thermoelectric generator. Geometry parameters, namely the height, the fill-ratio, the ratio of the cross-section area of n-type material over p-type material of thermoelectric module, solar concentration ratio, were analyzed under different operating conditions. In order to perform the analysis, an L27 (35) orthogonal array was employed to assess all of the design parameters returning the maximum output power. By the analysis of variance, the effect of each design parameter on the output power performance and the interaction between design parameters are identified. The optimal design parameter set is also obtained and it is found that the optimal design performs can potentially achieve 5.47 W output power compared with the output power of 1.95 W from the original design in most operating conditions.

This paper describes a low-cost, wide-range and multi-functional vision backend for Sailboat Research Testbed (SRT). SRTs are of great significance in autonomous sailing vessels (ASVs) research. The motivation behind this vision backend is the demand for various functions of an SRT, such as sailboat localization and control, yet the cost of building such a testbed should be economic. Hence, cost-effective hardware along with robust and lightweight vision algorithms are integrated into a vision backend to assist our SRT. This vision backend overcomes several inherent problems when applying some CV algorithms in the water environment, and presents multiple functionalities with high performance. This paper details our solutions and design of this vision backend. Moreover, a variety of schemes are introduced to reduce the cost when building SRTs.

Wind perception is crucial for autonomous sailboat which has features of long distance operation. Previously, anemometers based on thermal dynamics, acoustics or cup-vane anemometer have already been widely used, but they are generally large in size. This paper starts with vibration mechanics to develop a new kind of anemometer which is particularly suitable for mini-sized autonomous sailboats. An IMU which is fixed to one end of a non-rigid body, such as spring. The non-rigid body will vibrate if it is exposed to wind field. Physical quantities related to vibration can reflect different wind speeds. We modeled the new design and developed a prototype with a low cost. Experiments are conducted to collect data. Based on curve fitting of the experiment data, the wind speed is estimated with a mean error at 0.35 m/s for measuring range from 0 to 10.7 m/s.

Personal handwriting style fonts generation is a diverting but time-consuming task due to the large size of Chinese character set. In addition, unlike standard printed style fonts, hand-writing style fonts are of more complicated stroke and glyph feature. In this paper, an improved network architecture is proposed for learning and generation of personal hand-writing style fonts based on small character set. The network is composed of three sub-networks: 1) a classification network for identifying the general style of the target fonts; 2) a generating network for transferring the identified fonts to the target fonts; 3) a discriminating network for differentiating the generated image from real ones. The experiments revealed the effectiveness of the model for generating personal hand-writing style font with relatively small data size, reduction by a scale of 10 comparing to previous reported works.

This paper presents a new model of automatic music generation which is based on simulated annealing and genetic algorithm. Our model uses simulated annealing algorithm to create melody units on different chords, and regards them as the genes in genetic algorithm, which can pick out a fine combination of these genes. This model is efficient for producing massive fair-sounding pieces of double-track music, when provided with a customized metric. Hence, it can be especially useful for massively producing background musics for video games, or providing inspirations for music composers. In this paper, we detailedly state how to transform the prior knowledge about music theory into a reasonable metric, and propose a sample metric for reference. Using this sample metric, we generate a set of music pieces as test cases. The evaluation results show that these pieces fully satisfy the need of quality and creativity.

In this paper, we present an accurate approach to estimate vehicles' pose and shape from off-board multiview images. The images are taken by monocular cameras and have small overlaps. We utilize state-of-the-art convolutional neural networks (CNNs) to extract vehicles' semantic keypoints and introduce a Cross Projection Optimization (CPO) method to estimate the 3D pose. During the iterative CPO process, an adaptive shape adjustment method named Hierarchical Wireframe Constraint (HWC) is implemented to estimate the shape. Our approach is evaluated under both simulated and real-world scenes for performance verification. It's shown that our algorithm outperforms other existing monocular and stereo methods for vehicles' pose and shape estimation. This approach provides a new and robust solution for off-board visual vehicle localization and tracking, which can be applied to massive surveillance camera networks for intelligent transportation., Comment: 8 pages, 8 figures, published in ROBIO 2018

Trajectory tracking is a decisive factor that affects autonomous driving performance of mobile robots in real-world applications, such as industry, service and other areas. Nowadays, there has been many works about path planning and trajectory tracking. Whereas there are problems to be improved to make mobile robot well applied in practical world. For example, generated trajectory can't be tracked smoothly, and the robot has to stop and rotate itself to adjust pose and pass segments in trajectory because of constrains of path curvature and robot's kinematics model. In this paper, a new trajectory planning algorithm with cubic spline interpolation method was proposed, which fully considered constrains of robot model including velocity and acceleration bounds. And corresponding trajectory was generated. Then a robust controller was built to conduct tracking tests. Experimental results demonstrate that our planning and tracking algorithm could help robot achieve a smooth, accurate and efficient trajectory tracking performance without any stop.

In the field of autonomous driving, abundant researches have been carried out in development of advanced Lidar or vision algorithms for mapping and localization, and some efforts in the field of sensor fusion have been made to combine the advantages of multiple sensor types. However, most works focused on the 2D map construction, which had its own limitation with complex environments. In this paper, a new algorithm based on the fusion of Lidar and Inertial Measurement Unit (IMU) data is developed to construct a 2.5D map. We integrate the height information transformed from IMU sensor with laser scan results to construct a 2.5D occupied grid map. The proposed algorithm is convenient to implement on real-world mobile vehicles, and it is fast and robust. The effectiveness of our algorithm is validated by both simulation and practical experiment.

Leader-follower system could expand the load capacity in transport tasks. While few related literatures pay attention to the physical limitation and limit the maximum output velocity of designed controller. This paper expands a trajectory tracking controller with velocity constraints to leader-follower system. Leader and follower are both subjected to linear velocity constraint and angular velocity constraint due to the physical limitation. Selected trajectory tracking controller is applied in leader-follower system. Meanwhile, noises in reference trajectory of follower are released by Kalman filter. Then, a physical experiment platform with Turtlebots is established to verify this control scheme. Finally, experiment results of several examples proved the practicability of proposed control system. The velocity commands of this control system would not exceed the limitation of physical limitation.

Autonomous Surface Vehicles (ASVs) provide an effective way to actualize applications such as environment monitoring, search and rescue, and scientific researches. However, the conventional ASVs depends overly on the stored energy. Hybrid Sailboat, mainly powered by the wind, can solve this problem by using an auxiliary propulsion system. The electric energy cost of Hybrid Sailboat needs to be optimized to achieve the ocean automatic cruise mission. Based on adjusted setting on sails and rudders, this paper seeks the optimal trajectory for autonomic cruising to reduce the energy cost by changing the heading angle of sailing upwind. The experiment results validate the heading angle accounts for energy cost and the trajectory with the best heading angle saves up to 23.7% than other conditions. Furthermore, the energy-time line can be used to predict the energy cost for long-time sailing., 6pages, IEEE ROBIO 2018, accpeted

This paper investigates the cooperative moving-target enclosing control problem of networked unicycle-type nonholonomic vehicles with constant linear velocities. The information of the target is only known to some of the vehicles, and the topology of the vehicle network is described by a directed graph. A dynamic control law is proposed to steer the vehicles, such that they can get close to orbiting around the target while the target is moving with a time-vary velocity. Besides, the constraint of bounded angular velocity for the vehicles can always be satisfied. The proposed control law is distributed in the sense that each vehicle only uses its own information and the information of its neighbors in the network. Finally, simulation results of an example validate the effectiveness of the proposed control law.

In this paper, a new mechanical design of adaptive mini gripper has been proposed. This mini gripper is able to attach itself on a wide range of trees with different diameters and even some rough surfaces with bumps and asperities, due to its adaptive structure. Worm gear design enables its self-lock capbility when attaching itself to a surface, preventing it from falling down. Besides, self-lock property of worm gear also contributes to the energy saving ability. Furthermore the motion of the gripper is all active, which also improves the stability of the gripper. The structure is of $55 \mathrm {m}\mathrm {m}^{*} 55 \mathrm {m}\mathrm {m}^{*} 47\mathrm {m}\mathrm {m}$ in size, which is also an advantage to the wide use of this gripper. What’s more, this adaptive mini gripper weighs 79 grams, but it can hold 1700 grams in weight, more than 21.5 times of its own weight. In addition, the miniaturization work of the gripper contributes to mini size of climbing robots, and more work and practical use can be done with a much smaller size.

This paper introduces the tacking control of a low-cost mini-sized unmanned catamaran sailboat. Compared with traditional researches in sailboats based on acquiring wind speed and direction by a giant wind sensor and controlling the system by velocity polar diagram, to further increase the speed and motion agility, we propose an alternative way based on Force Polar Diagram (FPD). Thereafter, we propose a novel control algorithm to compute the sail angle that produces the maximum forward force along the boat‘s heading. We employ a 3-D force sensor to obtain the propelling force on the mast. FPD is created offline given the data collected from different apparent wind angles. In the experimental platform including a water pool, two electric fans generating a quasi-controllable time-invariant wind field and a camera for boat Iocalization, we conducted experiments and discovered that the proposed method increased the maximum speed by 56%, shortened the time by 44% and improved the motion agility in an autonomous tacking for upper wind motion.

Sailing robots provide a low-cost solution to conduct the ocean missions such as marine exploration, pollution detection, and border surveillance, etc. However, compared with other propeller-driven surface vessels, sailboat suffers in complex marine wind field due to its low mobility. Especially in tacking, sailboats are required to head upwind, and need to make a zig-zag path. In this trajectory, a series of turnings, which will cross the challenging no-go zone, place significant challenge as it will reduce speed greatly and consequently result in unsuccessful turning. This paper presents a hybrid sailboat design to solve this issue. Electric propellers and control system are added to a model sailboat. We have further designed the control strategy and tuned the parameters (PWM-time) experimentally. Finally, the system and control can complete the tacking maneuver with average speed approximately 10% higher and enhanced success rate, though the sailboat weight is much heavier.

Currently, AGVs (Auto Guided Vehicles) are the most widely used type of mobile robot in real world for logistics and intelligent manufacturing. While most of indoor AGVs do not have a special requirement on shock absorption systems, it remains a major concern for the outdoor AGVs' application. Compared with most of the current mono-spring absorption system designs, which means that all the spring dampers have identical elastic coefficient, dual-spring designs have an advantage in obstacle-crossing capability and shock absorption performances. This paper studies and validates the enhanced outdoor working performances of AGVs with dual-spring shock absorption systems. Theoretical dynamic analysis has been conduct to reveal the advantages in shock absorption characteristics. A series of simulation experiments have been performed to verify its advantages in stability and obstacle-crossing capabilities compared to conventional mono-spring absorption designs.

Recent studies have witnessed a significant progress in developing legged robots with rapid and stable locomotion speeds and adaptability to complex roads, but their high energy consumption limited their development and applications. This paper analyzes the energy efficiency of a bionic electric-drive panda robot serving as an emotional companion for robot-enhanced therapy. Unlike other quadruped robots, our bionic robot focuses on emotional interaction rather than capability of dexterous locomotion and operations. This results in the need to change working period. Then we proposed four strategies to reduce energy consumption. The energy efficiency optimization strategy described in this paper is suitable for quadruped robots focusing on none-highly dynamic motions, and can be treated as locomotion optimization strategy based on energy efficiency optimization for quadruped robots to some extent.

Accurate turning is not an easy task for the quadruped robot and previous work mainly addresses the problem with complex control strategy or systems. This paper proposes a design method for the accurate turning motion of a quadruped robot with 12 degrees of freedom (DOF). Unlike others, we have achieved precise turning motion with a relatively simple geometric approach. Once the parameters of desired movement are set, such as the turning radius and angles, the robot can realize corresponding circle locomotion. A design architecture including geometric analysis, 3D foot trajectory design and inverse kinematics is presented to solve the problem systematically. In addition, according to the different conditions, the corresponding compensation coefficient is necessarily considered in order to acquire precise values of leg joints. At last, comparison results by several experiments have identified the feasibility and accuracy of turning along a circle trajectory based on our proposed method.

A vision-based perception system for understanding the outdoor environment has been proposed. This system utilizes and applies the useful information from the binocular cameras of a legged robot for landform — terrain — ground environmental perception. The ground texture recognition can provide information about the material of the ground then a legged robot can choose an appropriate walking pose accordingly. With the terrain perception and obstacle detection, combined with semantic segmentation of the environment, a legged robot can move towards the target with intelligent obstacle avoidance strategy. Based on this vision-based perception system, we propose a vision-based perception framework for outdoor navigation tasks applicable to legged robots. In this framework, environmental modeling and situation assessment will be firstly carried out combined with multi-mode sensor fusion, and then footsteps and local path planning can be generated.

This paper presents the gait design and comparison study of a quadruped robot. The main contributions of this paper are: (i) Explore the modularized system design of an 8 degree-of-freedom quadruped robot with a power management system. (ii) Propose a gait design method based on drive function. (iii) Propose another gait design method based on foot trajectory. (iv) The simulation of the walk and trot gaits with above-mentioned methods are validated in Webots. (v) The walk and trot gait are successfully implemented in the real robot. Experimental results show that the stable locomotion can be achieved with improved elliptical foot trajectory.

Currently, the shock absorption system for outdoor AGV is mainly built with identical-spring solution, in which all the damping springs have the identical elastic coefficient. In this paper, we introduce a method to design the shock absorption system of the AGV using dual-spring solution. Springs of two different elastic coefficients are used, and an enhanced performance in obstacle-crossing capability can be achieved. The proposed dual-spring solution design method takes several critical outdoor working requirements as design constraints, and integrates damping system analysis to determine the optimal coefficients for the dual-spring system. To validate the effectiveness of this dual-spring design method, theoretical analysis is fully derived and a AGV chassis is physically built using dual-spring solution and is subjected to a series of validation tests.

In this paper, we propose a novel design of gaits for space manipulators so as to minimize the dynamic disturbance on a space station. Without modifying their joint configuration, we first propose the use of our previous developed gripping methodology. It combines the concepts of wheels motion in parallel grippers to reduce the swing motions in conventional gaits. For the proposed gaits, three major aspects are considered including 1) linear motion; 2) turning; and 3) exterior transition. Based on the conventional modeling approach for fixed base space manipulators, we extend the method to formulate the dynamic coupling during wheels motion. It is to visualize the manipulator as a prismatic joint with its gripping base moving with wheels motion. Also, we develop an experimental platform for verification. For disturbance analysis, various simulations have been conducted. Results have validated that the proposed gaits generate the lowest disturbance on a space station.

Ocean exploration has attracted enormous interest from human-kind for thousands of years. The sailing boat, propelled by wind is a historical invention. But human-involved marine exploration has high risk and low efficiency. This paper presents a new autonomous surface vehicle (ASV) based on retrofitting a trimaran sailing boat. The previous human-based maneuvering interfaces, i.e. sail and rudder control, are motorized by three electric actuators. The ASV acquires signals of wind speed and direction, GPS position, and rolling angle, determine the heading based on various wind direction. Experiments validates the effectiveness of the ASV.

Monocular cameras are not generally considered as a 3D measurement tool in the field of intelligent transportations. This belief limits the application of monocular cameras in many applications such as guiding robots or vehicles for autonomous driving. In this paper, we demonstrate that with the reference of a license plate, a monocular camera can be used as a tool to measure 3 dimensional parameters (width, height and length) of a passenger vehicle down to 10 cm accuracy. The proposed measurement method does not reply on any training process, but is designed as a fast and direct approach utilizing a series of fundamental computer vision techniques such as ROI extraction, edge/line detection, space coordinates transformations, etc. A series of validation tests were conducted and the results demonstrated the robustness of this measurement method and implies the possibility to broaden the application scope of monocular cameras in the field of autonomous driving and intelligent transportation systems.

Localization and navigation are fundamental issues to autonomous mobile robotics. In the case of the environmental map has been built, the traditional two-dimensional (2D) lidar localization and navigation system can't be matched to the initial position of the robot in dynamic environment and will be unreliable when kidnapping occurs. Moreover, it relies on high-cost lidar for high accuracy and long range. In view of this, the paper presents a low cost navigation system based on a low cost lidar and a cheap webcam. In this approach, 2D-codes are attached to the ceiling, to provide reference points to aid the indoor robot localization. The mobile robot is equipped with webcam pointing to the ceiling to identify 2D-codes. On the other hand, a low-cost 2D laser scanner is applied to build a map in unknown environment and detect obstacles. Adaptive Monte Carlo Localization (AMCL) is implements for lidar positioning, A* and Dynamic Window Approach (DWA) are applied in path planning based on a 2D grid map. The error analysis and experiments has validated the proposed method.

Space robots are in huge demand due to the rapid growth of their service targets, i.e., spacecraft. There are generally large flexible components on spacecraft, such as antenna reflectors and solar paddles. Due to the vibratility of their structure, it is challenging for a space robot with flexible appendages (the base is then called flexible-base) to capture and repair the large flexible spacecraft. After capturing, the two spacecraft with flexible appendages are connected by a space manipulator, and a compounded system is formed. In this paper, we developed a dynamic model and a closed-loop simulation system, to provide a means to verify path planning and control algorithms. Initially, the dynamic characteristics of different capturing stages (preimpact and post-impact) were analyzed. The topologies of a flexible-base space robot and the compounded system were described based on incidence and channel matrices. Secondly, the recursive dynamics was formulated and resolved by an effective numerical method. The modeling was verified by Adams’ model. Thirdly, we implemented a dynamics calculation block in Matlab/Simulink environment using the S-function package for the C program, and developed a closed-loop simulation system, which was composed of the Planning and Controller, the Multibody Dynamic, and the 3D Display modules. Finally, based on the simulation system, two typical missions—target berthing and on-orbital manipulation of the target along a circle, were simulated and evaluated. Dynamics analysis results presented some useful rules for the path planning and control to suppress the vibration of the flexible structure.

In this paper, a fast charging system (FCS) is designed for service robots. In this design, batteries are used to due to its energy density, whereas supercapacitors (SCs) are used to enhance the power density. DC-DC converter controls the FCS. The main advantage of the design of fast charging system is that, the SCs are charged with a large current fast and then discharge to the batteries with small current slowly. This feature is beneficial for batteries' long-life and store more energy for service robots which have been in great demand for multiple purposes, such as elderly care, child education etc. Some experimental and testing results are presented to validate the design of FCS for service robots.

This paper presents an omnidirectional steer-by-wire system for a four-wheel independent steering vehicle. The system consists of an extended steering interface and a behavior-based steering controller. The extended steering interface provides a novel manipulation way to vehicle driver. The driver can control the vehicle in traditional way or omnidirectionally without any mode switching operation. The reservation of the traditional driving way makes the driver adapt the novel steering interface easily. The steering interface also has a force-feedback function to synchronize the extended steering interface and the orientations of wheels so as to improve vehicle handling. The behavior-based steering controller is designed for controlling the orientations of wheels. It acts as virtual linkage among each wheel to minimize wheel slip resulted by the misalignment of wheels. As there is no trajectory planning needed in the control algorithm, the proposed controller is especially suitable for a nonautonomous vehicle, the driving path of which cannot be predetermined.

In this paper, we discuss the problem of how human control strategy can be represented as a parametric model using a support vector machine (SVM) and how an SVM-based controller can be used in controlling dynamically stable systems. The SVM approach has been implemented in the balance control of Gyrover, which is a dynamically stable, statically unstable, single-wheel mobile robot. The experimental results that compare SVM with general artificial neural network approaches clearly demonstrate the superiority of the SVM approach with regard to human control strategy learning.

This paper introduces a face detection, classification and counting system that is robust and works in real-time. It tracks multiple people, which is useful for face counting. The classification problem is defined as differentiating and then classifying the front of a face into Asian or non-Asian categories. The first step, is principal component analysis (PCA) for feature generation and independent component analysis (ICA) for feature extraction. Then, we employ support vector machine (SVM) for the training process and combine different SVM classifiers to create new classifiers, which improves the classification rate. Based on this, we can count the number of Asians and non-Asians. Experiments show that our system achieves a classification rate of 82.5% based on a database containing 750 face images from FERET.

With the emerging need for household applications, service robotics has become a hot spot attracting researchers globally. Universities, institutes, and industrial companies, either independently or collaboratively, have been focusing on research and development for household service robots, resulting in interesting and well-performing household service robotic systems. In this chapter, we first give a categorization of the various applications, followed by an elaboration of some highlighted cases with their overall system designs.

Mapping, localization, and navigation are functions necessitated by a diverse range of household service robot solutions. This chapter presents a wide variety of mapping, localization, and navigation techniques that suit a wide range of robot platforms and applications. The problem of mapping and localization has been approached in many ways and we review successful results attained by traditional radio tracking, ultra wideband sensing, RFID communication, North-Star infrared sensing, two-dimensional special pattern detection, laser-range surveying, various camera system sensing, time-of-flight camera ranging, and finally low-cost contact and near-field sensing. The problem of navigation, path planning, and obstacle avoidance requires not only sensing described above but adequate robot responses in a dynamic situation. There are many approaches to successful obstacle avoidance and our review of the literature covers the use of structured light as well as linear and planar sensors, along with visual processing techniques such as optic flow, ground plane segmentation, and feature-based obstacle avoidance, in addition to the optimization of path planning, robot interaction, and behavior.

Human–robot interaction (HRI) studies on how humans collaborate and interact with robots in an effective and natural way have received considerable attention in the robot research community, especially with regard to the design and development of household service robots, owing to their highly interactive characteristics in domestic service activities. Many researchers have proposed a variety of principles, algorithms, and systems to achieve an effective and natural HRI in the domestic environment. In this chapter, we first give a brief illustration of the state of the art for HRI, divided into several categories, and then elaborate on some selected cases with regard to the design and implementation of HRI systems.

Robotic grasping and manipulation comprise three subtasks, i.e., target detection, planning, and control. The robot first needs to detect the target. Here “detect” means to find (or recognize) the target and locate it. The target could be the object to be manipulated (e.g., electrical plugs) or the destination of the object (electrical sockets). Then the robot approaches the target in an optimized trajectory. In the process of approaching and grasping, the robot should be controlled to perform the task correctly and smoothly. In this chapter, we review the approaches to accomplish these three subtasks, i.e., target detection, planning, and control.

With the significant development of robotic technologies, the applications of robots have been extended broadly from their traditional industry role to military, medical field, and even daily services. Robotics has gradually become a very large industry with tremendous influence on the sustainable development of the world.

To provide a high starting torque and to work under a high rpm range are the design requirements for the integrated startgenerators (ISG) used for intelligent vehicles with hybrid powertrains. However, meeting with both of these two requirements usually involves with sophisticated motor and controller design and high manufacturing cost. Hence, a transmission with variable reduction ratio is desired to be configured between the ISG and the engine. In an earlier paper, a Controller-Free Ratio-Variable gearbox design concept has been introduced, which can auto change gear ratios in a purely mechanical way and avoid from using any controller or actuators. This paper represents the work on implementation, testing and evaluation of the gearbox. The performance of the gearbox proof to be functional though the test result.

Electronic devices (PCs, smart phones, etc.) are ubiquitous in the world and the convenience in users' input has become increasingly important for their extensive applications. Disabled armless people are also in need of a novel input interface for a better life. In this paper, we present our research on a wearable sensor-integrated shoe system as a writing platform, by sensing and analyzing the foot movement, so it enables people to write by foot. Also using this system, people can exercise their lower limbs and related brain parts for recovery from illness, e.g. stroke. We use the force sensors (FSRs) to localize the foot when it attacks ground, i.e. touching ground from air. This system classifies FSRs data by BP neural network to obtain the start point for each basic stroke. Also the force sensor can classify the location of stroke starting point from another aspect. Finally, low cost optical tracking sensor is used to draw the stroke. Experiments validate the design of the shoe writing system.