Search

Your search keyword '"Mohammadi, Ali"' showing total 32 results
Start Over Author "Mohammadi, Ali" Publication Year Range Last 3 years Publisher ieee
32 results on '"Mohammadi, Ali"'

20. FIG-OP: Exploring Large-Scale Unknown Environments on a Fixed Time Budget

Author

Peltzer, Oriana, primary, Bouman, Amanda, additional, Kim, Sung-Kyun, additional, Senanayake, Ransalu, additional, Ott, Joshua, additional, Delecki, Harrison, additional, Sobue, Mamoru, additional, Kochenderfer, Mykel J., additional, Schwager, Mac, additional, Burdick, Joel, additional, and Agha-mohammadi, Ali-akbar, additional

Published
2022
Full Text
View/download PDF

22. Belief Space Planning: a Covariance Steering Approach

Author

Zheng, Dongliang, Ridderhof, Jack, Tsiotras, Panagiotis, and Agha-mohammadi, Ali-akbar

Subjects
FOS: Computer and information sciences, Computer Science - Robotics, FOS: Electrical engineering, electronic engineering, information engineering, Systems and Control (eess.SY), Robotics (cs.RO), Electrical Engineering and Systems Science - Systems and Control
Abstract

A new belief space planning algorithm, called covariance steering Belief RoadMap (CS-BRM), is introduced, which is a multi-query algorithm for motion planning of dynamical systems under simultaneous motion and observation uncertainties. CS-BRM extends the probabilistic roadmap (PRM) approach to belief spaces and is based on the recently developed theory of covariance steering (CS) that enables guaranteed satisfaction of terminal belief constraints in finite-time. The nodes in the CS-BRM are sampled in belief space and represent distributions of the system states. A covariance steering controller steers the system from one BRM node to another, thus acting as an edge controller of the corresponding belief graph that ensures belief constraint satisfaction. After the edge controller is computed, a specific edge cost is assigned to that edge. The CS-BRM algorithm allows the sampling of non-stationary belief nodes, and thus is able to explore the velocity space and find efficient motion plans. The performance of CS-BRM is evaluated and compared to a previous belief space planning method, demonstrating the benefits of the proposed approach.

Published
2022

25. A Novel TCP/IP Header Hijacking Attack on SDN

Author

Mohammadi, Ali Akbar, primary, Hussain, Rasheed, additional, Oracevic, Alma, additional, Kazmi, Syed Muhammad Ahsan Raza, additional, Hussain, Fatima, additional, Aloqaily, Moayad, additional, and Son, Junggab, additional

Published
2022
Full Text
View/download PDF

26. Unsupervised Monocular Depth Learning with Integrated Intrinsics and Spatio-Temporal Constraints

Author

Chen, Kenny, Pogue, Alexandra, Lopez, Brett T., Agha-mohammadi, Ali-akbar, and Mehta, Ankur

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Robotics, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Robotics (cs.RO), Machine Learning (cs.LG)
Abstract

Monocular depth inference has gained tremendous attention from researchers in recent years and remains as a promising replacement for expensive time-of-flight sensors, but issues with scale acquisition and implementation overhead still plague these systems. To this end, this work presents an unsupervised learning framework that is able to predict at-scale depth maps and egomotion, in addition to camera intrinsics, from a sequence of monocular images via a single network. Our method incorporates both spatial and temporal geometric constraints to resolve depth and pose scale factors, which are enforced within the supervisory reconstruction loss functions at training time. Only unlabeled stereo sequences are required for training the weights of our single-network architecture, which reduces overall implementation overhead as compared to previous methods. Our results demonstrate strong performance when compared to the current state-of-the-art on multiple sequences of the KITTI driving dataset and can provide faster training times with its reduced network complexity., Accepted to the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021), Prague, Czech Republic

Published
2021

30. Learning-Aided Asynchronous ADMM for Optimal Power Flow.

Author

Mohammadi, Ali and Kargarian, Amin

Subjects
*ELECTRICAL load, *DISTRIBUTED algorithms, *LAGRANGE multiplier, *TEST systems, *MATHEMATICAL optimization, *EXTRAPOLATION
Abstract

The synchronization requirement is a bottleneck of many distributed optimization algorithms, particularly for solving problems with computationally heterogeneous subproblems and during the occurrence of communication failure/delay. This paper presents a double-loop learning-aided asynchronous alternating direction method of multipliers (LA-ADMM) that has information prediction capability and handles a considerable level of asynchrony between subproblems. A momentum-extrapolation prediction-correction technique is developed to enable subproblems to predict their neighbors missing shared variable information instead of using the latest received values. An online streaming-based anomaly classification is designed to observe the performance of predicted data and control Lagrange multipliers update over the course of iterations. The proposed LA-ADMM reduces under-utilization of computation resources, especially if subproblems are computationally heterogeneous. This algorithm also enhances distributed optimization robustness against communication failure/delay that may result in a considerable level of asynchrony between subproblems. LA-ADMM is applied to solve the optimal power flow problem for several test systems. Promising results are obtained as compared to the classical synchronous ADMM and asynchronous ADMM without the anomaly switch control. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

31. Dual Band, Miniaturized Permittivity Measurement Sensor With Negative-Order SIW Resonator.

Author

Mohammadi, Pejman, Teimouri, Hadi, Mohammadi, Ali, Demir, Simsek, and Kara, Ali

Abstract

A novel dual band, highly sensitive Substrate Integrated Waveguide (SIW) sensor for permittivity measurements is presented. A pair of modified Complementary Split Ring Resonators (CSRRs) is etched on SIW surface. CSRRs are located in the center of SIW, where the electric field distribution is high so that the coupling be maximized. The coupling between the SIW and the CSRRs as well as the adjacent CSRRs results in two notches in transmission coefficient. These notches vary with the dielectric loading on the sensor. The ratio of a notch variation to the load permittivity variation determines the sensitivity of proposed sensor. Two sensitivities proportional to two notches are provided. Normalized sensitivities from both notches show identical values. Therefore, any environmental effect have the same variation on the TZs. This demonstrates the potential of the proposed sensor for differential operation that can mitigate the effect of environmental condition. The size of the proposed sensor is small as the inductive and the capacitive effects of CSRRs forced the SIW to operate below the cut off frequency at negative-order-resonance mode. All design steps including SIW design, CSRRs design and modified CSRRs effects are presented in details. The sensor operation principle is described through an equivalent circuit model as well as simulation results. The experimental results indicates that the normalized sensitivity is 3.4% which is much higher than similar sensors. The prototype sensor size ($27.8\times 18.4\times 0.508$ mm3) is smaller than those reported in the literature. [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

32. Compact Size, and Highly Sensitive, Microwave Sensor for Non-Invasive Measurement of Blood Glucose Level.

Author

Mohammadi, Pejman, Mohammadi, Ali, Demir, Simsek, and Kara, Ali

Abstract

None-invasive blood glucose measurement enables effective diagnosis and treatment of diabetic patients. The existing microwave sensors suffer from low sensitivity and large size. This article presents a highly sensitive and compact size non-invasive microwave sensor for real-time blood glucose measurements. We have developed a new sensing technique using directly connected Branch Line Coupler and Split Ring Resonators. This technique significantly improves the sensitivity by mitigating the limited coupling between transmission lines and resonators. In addition, using Split Ring Resonators reduces the sensor size due to capacitive and inductive effects, which are loaded to the Branch Line Coupler. The proposed sensing function is based on shifting the transmission notch frequency in coupled arm of the Branch Line Coupler, which is caused by loading the Split Ring Resonators with varying glucose concentration. A prototype sensor is fabricated and successfully tested using several glucose concentrations in deionized water. Experimental results demonstrate 0.72 MHz/mgdL−1 measurement sensitivity, which is higher in comparison with available sensors in PCB technology. The prototype sensor size is $3.5\times 3.5\times 0.16$ cm3. [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results