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2020 – today
- 2024
[j13]Chungwei Lin
, Yebin Wang, William T. Vetterling, Devesh K. Jha, Rien Quirynen:
Path Generation Based on Electrostatic Equipotential Curves. IEEE Access 12: 55019-55032 (2024)- [j12]Kei Ota, Devesh K. Jha, Asako Kanezaki:
A framework for training larger networks for deep Reinforcement learning. Mach. Learn. 113(9): 6115-6139 (2024) - [j11]Yuki Shirai, Devesh K. Jha, Arvind U. Raghunathan:
Robust Pivoting Manipulation Using Contact Implicit Bilevel Optimization. IEEE Trans. Robotics 40: 3425-3444 (2024) - [c49]Xinghao Zhu, Devesh K. Jha, Diego Romeres, Lingfeng Sun, Masayoshi Tomizuka, Anoop Cherian:
Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection. ICRA 2024: 816-823 - [c48]Boyuan Liang, Kei Ota, Masayoshi Tomizuka, Devesh K. Jha:
Robust In-Hand Manipulation with Extrinsic Contacts. ICRA 2024: 6544-6550 - [c47]Kei Ota, Devesh K. Jha, Krishna Murthy Jatavallabhula, Asako Kanezaki, Joshua B. Tenenbaum:
Tactile Estimation of Extrinsic Contact Patch for Stable Placement. ICRA 2024: 13876-13882 - [c46]Lingfeng Sun, Devesh K. Jha, Chiori Hori, Siddarth Jain, Radu Corcodel, Xinghao Zhu, Masayoshi Tomizuka, Diego Romeres:
Interactive Planning Using Large Language Models for Partially Observable Robotic Tasks. ICRA 2024: 14054-14061 - [i46]Guoxiang Zhao, Devesh K. Jha, Yebin Wang, Minghui Zhu:
iPolicy: Incremental Policy Algorithms for Feedback Motion Planning. CoRR abs/2401.02883 (2024) - [i45]Boyuan Liang, Kei Ota, Masayoshi Tomizuka, Devesh K. Jha:
Robust In-Hand Manipulation with Extrinsic Contacts. CoRR abs/2403.18960 (2024) - [i44]Kei Ota, Devesh K. Jha, Siddarth Jain, Bill Yerazunis, Radu Corcodel, Yash Shukla, Antonia Bronars, Diego Romeres:
Autonomous Robotic Assembly: From Part Singulation to Precise Assembly. CoRR abs/2406.05331 (2024) - [i43]Mengchao Zhang, Devesh K. Jha, Arvind U. Raghunathan, Kris Hauser:
Simultaneous Trajectory Optimization and Contact Selection for Contact-rich Manipulation with High-Fidelity Geometry. CoRR abs/2407.16976 (2024) - 2023
- [j10]Wanlin Li, Meng Wang, Jiarui Li, Yao Su, Devesh K. Jha, Xinyuan Qian, Kaspar Althoefer, Hangxin Liu:
L$^{3}$ F-TOUCH: A Wireless GelSight With Decoupled Tactile and Three-Axis Force Sensing. IEEE Robotics Autom. Lett. 8(8): 5148-5155 (2023) - [c45]Yuki Shirai, Devesh K. Jha, Arvind U. Raghunathan, Diego Romeres:
Chance-Constrained Optimization in Contact-rich Systems. ACC 2023: 14-21 - [c44]Devesh K. Jha, Siddarth Jain, Diego Romeres, William Yerazunis, Daniel Nikovski:
Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control. ECC 2023: 1-8 - [c43]Devesh K. Jha, Diego Romeres, Siddarth Jain, William Yerazunis, Daniel Nikovski:
Design of Adaptive Compliance Controllers for Safe Robotic Assembly. ECC 2023: 1-8 - [c42]Yuki Shirai, Devesh K. Jha, Arvind U. Raghunathan:
Covariance Steering for Uncertain Contact-rich Systems. ICRA 2023: 7923-7929 - [c41]Sangwoon Kim, Devesh K. Jha, Diego Romeres, Parag Patre, Alberto Rodriguez:
Simultaneous Tactile Estimation and Control of Extrinsic Contact. ICRA 2023: 12563-12569 - [c40]Yuki Shirai, Devesh K. Jha, Arvind U. Raghunathan, Dennis W. Hong:
Tactile Tool Manipulation. ICRA 2023: 12597-12603 - [c39]Chiori Hori, Puyuan Peng, David Harwath, Xinyu Liu, Kei Ota, Siddarth Jain, Radu Corcodel, Devesh K. Jha, Diego Romeres, Jonathan Le Roux:
Style-transfer based Speech and Audio-visual Scene understanding for Robot Action Sequence Acquisition from Videos. INTERSPEECH 2023: 4663-4667 - [c38]Seiji Shaw, Devesh K. Jha, Arvind U. Raghunathan, Radu Corcodel, Diego Romeres, George Konidaris, Daniel Nikovski:
Constrained Dynamic Movement Primitives for Collision Avoidance in Novel Environments. IROS 2023: 3672-3679 - [c37]Kei Ota, Devesh K. Jha, Hsiao-Yu Tung, Joshua B. Tenenbaum:
Tactile-Filter: Interactive Tactile Perception for Part Mating. Robotics: Science and Systems 2023 - [c36]Mengchao Zhang, Devesh K. Jha, Arvind U. Raghunathan, Kris Hauser:
Simultaneous Trajectory Optimization and Contact Selection for Multi-Modal Manipulation Planning. Robotics: Science and Systems 2023 - [i42]Yuki Shirai, Devesh K. Jha, Arvind U. Raghunathan, Dennis W. Hong:
Tactile Tool Manipulation. CoRR abs/2301.06698 (2023) - [i41]Sangwoon Kim, Devesh K. Jha, Diego Romeres, Parag Patre, Alberto Rodriguez:
Simultaneous Tactile Estimation and Control of Extrinsic Contact. CoRR abs/2303.03385 (2023) - [i40]Kei Ota, Devesh K. Jha, Hsiao-Yu Tung, Joshua B. Tenenbaum:
Tactile-Filter: Interactive Tactile Perception for Part Mating. CoRR abs/2303.06034 (2023) - [i39]Yuki Shirai, Devesh K. Jha, Arvind U. Raghunathan:
Robust Pivoting Manipulation using Contact Implicit Bilevel Optimization. CoRR abs/2303.08965 (2023) - [i38]Yuki Shirai, Devesh K. Jha, Arvind U. Raghunathan:
Covariance Steering for Uncertain Contact-rich Systems. CoRR abs/2303.13382 (2023) - [i37]Eric Rosen, Devesh K. Jha:
A Virtual Reality Teleoperation Interface for Industrial Robot Manipulators. CoRR abs/2305.10960 (2023) - [i36]Mengchao Zhang, Devesh K. Jha, Arvind U. Raghunathan, Kris Hauser:
Simultaneous Trajectory Optimization and Contact Selection for Multi-Modal Manipulation Planning. CoRR abs/2306.06465 (2023) - [i35]Chiori Hori, Puyuan Peng, David Harwath, Xinyu Liu, Kei Ota, Siddarth Jain, Radu Corcodel, Devesh K. Jha, Diego Romeres, Jonathan Le Roux:
Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos. CoRR abs/2306.15644 (2023) - [i34]Kei Ota, Devesh K. Jha, Krishna Murthy Jatavallabhula, Asako Kanezaki, Joshua B. Tenenbaum:
Tactile Estimation of Extrinsic Contact Patch for Stable Placement. CoRR abs/2309.14552 (2023) - [i33]Lingfeng Sun, Devesh K. Jha, Chiori Hori, Siddarth Jain, Radu Corcodel, Xinghao Zhu, Masayoshi Tomizuka, Diego Romeres:
Interactive Planning Using Large Language Models for Partially Observable Robotics Tasks. CoRR abs/2312.06876 (2023) - [i32]Xinghao Zhu, Devesh K. Jha, Diego Romeres, Lingfeng Sun, Masayoshi Tomizuka, Anoop Cherian:
Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection. CoRR abs/2312.10571 (2023) - 2022
- [c35]Arvind U. Raghunathan, Devesh K. Jha, Diego Romeres:
Homogeneous Infeasible Interior Point Method for Convex Quadratic Programs. CDC 2022: 7571-7578 - [c34]Devesh K. Jha, Diego Romeres, William Yerazunis, Daniel Nikovski:
Imitation and Supervised Learning of Compliance for Robotic Assembly. ECC 2022: 1882-1889 - [c33]Arvind U. Raghunathan, Devesh K. Jha, Diego Romeres:
PyROBOCOP: Python-based Robotic Control & Optimization Package for Manipulation. ICRA 2022: 985-991 - [c32]Yuki Shirai, Devesh K. Jha, Arvind U. Raghunathan, Diego Romeres:
Robust Pivoting: Exploiting Frictional Stability Using Bilevel Optimization. ICRA 2022: 992-998 - [c31]Tim Schneider, Boris Belousov, Georgia Chalvatzaki, Diego Romeres, Devesh K. Jha, Jan Peters:
Active Exploration for Robotic Manipulation. IROS 2022: 9355-9362 - [i31]Yuki Shirai, Devesh K. Jha, Arvind U. Raghunathan, Diego Romeres:
Chance-Constrained Optimization in Contact-Rich Systems for Robust Manipulation. CoRR abs/2203.02616 (2022) - [i30]Arvind U. Raghunathan, Devesh K. Jha, Diego Romeres:
PYROBOCOP: Python-based Robotic Control & Optimization Package for Manipulation. CoRR abs/2203.10013 (2022) - [i29]Eric Rosen, Sreehari Rammohan, Devesh K. Jha:
Learning robot motor skills with mixed reality. CoRR abs/2203.11324 (2022) - [i28]Yuki Shirai, Devesh K. Jha, Arvind U. Raghunathan, Diego Romeres:
Robust Pivoting: Exploiting Frictional Stability Using Bilevel Optimization. CoRR abs/2203.11412 (2022) - [i27]Devesh K. Jha, Diego Romeres, Siddarth Jain, William Yerazunis, Daniel Nikovski:
Design of Adaptive Compliance Controllers for Safe Robotic Assembly. CoRR abs/2204.10447 (2022) - [i26]Seiji Shaw, Devesh K. Jha, Arvind U. Raghunathan, Radu Corcodel, Diego Romeres, George Konidaris, Daniel Nikovski:
Constrained Dynamic Movement Primitives for Safe Learning of Motor Skills. CoRR abs/2209.14461 (2022) - [i25]Tim Schneider, Boris Belousov, Georgia Chalvatzaki, Diego Romeres, Devesh K. Jha, Jan Peters:
Active Exploration for Robotic Manipulation. CoRR abs/2210.12806 (2022) - [i24]Devesh K. Jha, Siddarth Jain, Diego Romeres, William Yerazunis, Daniel Nikovski:
Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control. CoRR abs/2212.01434 (2022) - 2021
- [j9]Kei Ota, Devesh K. Jha, Diego Romeres, Jeroen van Baar, Kevin A. Smith, Takayuki Semitsu, Tomoaki Oiki, Alan Sullivan, Daniel Nikovski, Joshua B. Tenenbaum:
Data-Efficient Learning for Complex and Real-Time Physical Problem Solving Using Augmented Simulation. IEEE Robotics Autom. Lett. 6(2): 4241-4248 (2021) - [j8]Ankush Chakrabarty, Devesh K. Jha, Gregery T. Buzzard, Yebin Wang, Kyriakos G. Vamvoudakis:
Safe Approximate Dynamic Programming via Kernelized Lipschitz Estimation. IEEE Trans. Neural Networks Learn. Syst. 32(1): 405-419 (2021) - [c30]Siyuan Dong, Devesh K. Jha, Diego Romeres, Sangwoon Kim, Daniel Nikovski, Alberto Rodriguez:
Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry. ICRA 2021: 6437-6443 - [c29]Shiyu Jin, Diego Romeres, Arvind Ragunathan, Devesh K. Jha, Masayoshi Tomizuka:
Trajectory Optimization for Manipulation of Deformable Objects: Assembly of Belt Drive Units. ICRA 2021: 10002-10008 - [i23]Kei Ota, Devesh K. Jha, Asako Kanezaki:
Training Larger Networks for Deep Reinforcement Learning. CoRR abs/2102.07920 (2021) - [i22]Devesh K. Jha:
Markov Modeling of Time-Series Data using Symbolic Analysis. CoRR abs/2103.11238 (2021) - [i21]Siyuan Dong, Devesh K. Jha, Diego Romeres, Sangwoon Kim, Daniel Nikovski, Alberto Rodriguez:
Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry. CoRR abs/2104.01167 (2021) - [i20]Shiyu Jin, Diego Romeres, Arvind Ragunathan, Devesh K. Jha, Masayoshi Tomizuka:
Trajectory Optimization for Manipulation of Deformable Objects: Assembly of Belt Drive Units. CoRR abs/2106.00898 (2021) - [i19]Devesh K. Jha:
Distributed Task Allocation in Homogeneous Swarms Using Language Measure Theory. CoRR abs/2106.02992 (2021) - [i18]Arvind U. Raghunathan, Devesh K. Jha, Diego Romeres:
PYROBOCOP : Python-based Robotic Control & Optimization Package for Manipulation and Collision Avoidance. CoRR abs/2106.03220 (2021) - [i17]Devesh K. Jha, Diego Romeres, William Yerazunis, Daniel Nikovski:
Imitation and Supervised Learning of Compliance for Robotic Assembly. CoRR abs/2111.10488 (2021) - 2020
- [j7]Alberto Dalla Libera, Diego Romeres, Devesh K. Jha, Bill Yerazunis, Daniel Nikovski:
Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements. IEEE Robotics Autom. Lett. 5(2): 3548-3555 (2020) - [c28]Kei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki, Yusuke Yoshiyasu, Yoko Sasaki, Toshisada Mariyama, Daniel Nikovski:
Deep Reactive Planning in Dynamic Environments. CoRL 2020: 1943-1957 - [c27]Kei Ota, Tomoaki Oiki, Devesh K. Jha, Toshisada Mariyama, Daniel Nikovski:
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning? ICML 2020: 7424-7433 - [c26]Patrik Kolaric, Devesh K. Jha, Arvind U. Raghunathan, Frank L. Lewis, Mouhacine Benosman, Diego Romeres, Daniel Nikovski:
Local Policy Optimization for Trajectory-Centric Reinforcement Learning. ICRA 2020: 5094-5100 - [c25]Kei Ota, Yoko Sasaki, Devesh K. Jha, Yusuke Yoshiyasu, Asako Kanezaki:
Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path. IROS 2020: 6061-6068 - [c24]Wenyu Zhang, Skyler Seto, Devesh K. Jha:
CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context. IROS 2020: 7131-7138 - [c23]Keisuke Kojima, Mohammad H. Tahersima, Toshiaki Koike-Akino, Devesh K. Jha, Yingheng Tang, Ye Wang, Kieran Parsons, Fengqiao Sang, Jonathan Klamkin:
Deep Neural Networks for Designing Integrated Photonics. OFC 2020: 1-3 - [c22]Yingheng Tang, Keisuke Kojima, Toshiaki Koike-Akino, Ye Wang, Pengxiang Wu, Mohammad H. Tahersima, Devesh K. Jha, Kieran Parsons, Minghao Qi:
Generative Deep Learning Model for a Multi-Level Nano-Optic Broadband Power Splitter. OFC 2020: 1-3 - [i16]Patrik Kolaric, Devesh K. Jha, Arvind U. Raghunathan, Frank L. Lewis, Mouhacine Benosman, Diego Romeres, Daniel Nikovski:
Local Policy Optimization for Trajectory-Centric Reinforcement Learning. CoRR abs/2001.08092 (2020) - [i15]Wenyu Zhang, Devesh K. Jha, Emil Laftchiev, Daniel Nikovski:
Multi-label Prediction in Time Series Data using Deep Neural Networks. CoRR abs/2001.10098 (2020) - [i14]Alberto Dalla Libera, Diego Romeres, Devesh K. Jha, Bill Yerazunis, Daniel Nikovski:
Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements. CoRR abs/2002.10621 (2020) - [i13]Kei Ota, Tomoaki Oiki, Devesh K. Jha, Toshisada Mariyama, Daniel Nikovski:
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning? CoRR abs/2003.01629 (2020) - [i12]Kei Ota, Yoko Sasaki, Devesh K. Jha, Yusuke Yoshiyasu, Asako Kanezaki:
Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path. CoRR abs/2003.01641 (2020) - [i11]Wenyu Zhang, Skyler Seto, Devesh K. Jha:
CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context. CoRR abs/2003.11696 (2020) - [i10]Yifang Liu, Diego Romeres, Devesh K. Jha, Daniel Nikovski:
Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks. CoRR abs/2007.11646 (2020) - [i9]Kei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki, Yusuke Yoshiyasu, Yoko Sasaki, Toshisada Mariyama, Daniel Nikovski:
Deep Reactive Planning in Dynamic Environments. CoRR abs/2011.00155 (2020) - [i8]Kei Ota, Devesh K. Jha, Diego Romeres, Jeroen van Baar, Kevin A. Smith, Takayuki Semitsu, Tomoaki Oiki, Alan Sullivan, Daniel Nikovski, Joshua B. Tenenbaum:
Towards Human-Level Learning of Complex Physical Puzzles. CoRR abs/2011.07193 (2020)
2010 – 2019
- 2019
- [j6]Nurali Virani, Devesh K. Jha, Asok Ray, Shashi Phoha:
Sequential hypothesis tests for streaming data via symbolic time-series analysis. Eng. Appl. Artif. Intell. 81: 234-246 (2019) - [c21]Ankush Chakrabarty, Devesh K. Jha, Yebin Wang:
Data-Driven Control Policies for Partially Known Systems via Kernelized Lipschitz Learning. ACC 2019: 4192-4197 - [c20]Devesh K. Jha, Arvind U. Raghunathan, Diego Romeres:
Quasi-Newton Trust Region Policy Optimization. CoRL 2019: 945-954 - [c19]Diego Romeres, Devesh K. Jha, William Yerazunis, Daniel Nikovski, Hoang Anh Dau:
Anomaly Detection for Insertion Tasks in Robotic Assembly Using Gaussian Process Models. ECC 2019: 1017-1022 - [c18]Arvind U. Raghunathan, Anoop Cherian, Devesh K. Jha:
Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function. ICML 2019: 5291-5300 - [c17]Diego Romeres, Devesh K. Jha, Alberto Dalla Libera, Bill Yerazunis, Daniel Nikovski:
Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze. ICRA 2019: 3195-3202 - [c16]Jeroen van Baar, Alan Sullivan, Radu Cordorel, Devesh K. Jha, Diego Romeres, Daniel Nikovski:
Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics. ICRA 2019: 6001-6007 - [c15]Kei Ota, Devesh K. Jha, Tomoaki Oiki, Mamoru Miura, Takashi Nammoto, Daniel Nikovski, Toshisada Mariyama:
Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning. IROS 2019: 3487-3494 - [c14]Mohammad H. Tahersima, Keisuke Kojima, Toshiaki Koike-Akino, Devesh K. Jha, Bingnan Wang, Chungwei Lin, Kieran Parsons:
Deep Neural Network Inverse Modeling for Integrated Photonics. OFC 2019: 1-3 - [i7]Kei Ota, Devesh K. Jha, Tomoaki Oiki, Mamoru Miura, Takashi Nammoto, Daniel Nikovski, Toshisada Mariyama:
Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning. CoRR abs/1903.05751 (2019) - [i6]Arvind U. Raghunathan, Anoop Cherian, Devesh K. Jha:
Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function. CoRR abs/1905.05927 (2019) - [i5]Ankush Chakrabarty, Devesh K. Jha, Gregery T. Buzzard, Yebin Wang, Kyriakos G. Vamvoudakis:
Safe Approximate Dynamic Programming Via Kernelized Lipschitz Estimation. CoRR abs/1907.02151 (2019) - [i4]Jonathan Chang, Nishanth Kumar, Sean Hastings, Aaron Gokaslan, Diego Romeres, Devesh K. Jha, Daniel Nikovski, George Dimitri Konidaris, Stefanie Tellex:
Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control. CoRR abs/1910.10628 (2019) - [i3]Devesh K. Jha, Arvind U. Raghunathan, Diego Romeres:
Quasi-Newton Trust Region Policy Optimization. CoRR abs/1912.11912 (2019) - 2018
- [j5]Devesh K. Jha, Nurali Virani, Jan Reimann, Abhishek Srivastav, Asok Ray:
Symbolic analysis-based reduced order Markov modeling of time series data. Signal Process. 149: 68-81 (2018) - [j4]Yue Li, Devesh K. Jha, Asok Ray, Thomas A. Wettergren:
Information-Theoretic Performance Analysis of Sensor Networks via Markov Modeling of Time Series Data. IEEE Trans. Cybern. 48(6): 1898-1909 (2018) - [c13]Devesh K. Jha:
Algorithms for Task Allocation in Homogeneous Swarm of Robots. IROS 2018: 3771-3776 - [p1]Devesh K. Jha, Nurali Virani, Asok Ray:
Markov Modeling of Time Series via Spectral Analysis for Detection of Combustion Instabilities. Handbook of Dynamic Data Driven Applications Systems 2018: 123-138 - [i2]Jeroen van Baar, Alan Sullivan, Radu Cordorel, Devesh K. Jha, Diego Romeres, Daniel Nikovski:
Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics. CoRR abs/1809.04720 (2018) - [i1]Diego Romeres, Devesh K. Jha, Alberto Dalla Libera, William Yerazunis, Daniel Nikovski:
Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze. CoRR abs/1809.04993 (2018) - 2017
- [j3]Yue Li, Devesh K. Jha, Asok Ray, Thomas A. Wettergren:
Information Fusion of Passive Sensors for Detection of Moving Targets in Dynamic Environments. IEEE Trans. Cybern. 47(1): 93-104 (2017) - [c12]Yebin Wang, Devesh K. Jha, Yukiyasu Akemi:
A two-stage RRT path planner for automated parking. CASE 2017: 496-502 - [c11]Devesh K. Jha, Daniel Nikovski, William Yerazunis, Amir-massoud Farahmand:
Learning to regulate rolling ball motion. SSCI 2017: 1-6 - 2016
- [j2]Devesh K. Jha, Pritthi Chattopadhyay, Soumik Sarkar, Asok Ray:
Path planning in GPS-denied environments via collective intelligence of distributed sensor networks. Int. J. Control 89(5): 984-999 (2016) - [c10]Yusuke Seto, Noboru Takahashi, Devesh K. Jha, Nurali Virani, Asok Ray:
Data-driven robot gait modeling via symbolic time series analysis. ACC 2016: 3904-3909 - [c9]Soumalya Sarkar, Devesh K. Jha, Kin Gwn Lore, Soumik Sarkar, Asok Ray:
Multimodal spatiotemporal information fusion using neural-symbolic modeling for early detection of combustion instabilities. ACC 2016: 4918-4923 - [c8]Yue Li, Devesh K. Jha, Asok Ray, Thomas A. Wettergren:
Sensor selection for passive sensor networks in dynamic environment: A dynamic data-driven approach. ACC 2016: 4924-4929 - [c7]Devesh K. Jha, Minghui Zhu, Yebin Wang, Asok Ray:
Data-driven anytime algorithms for motion planning with safety guarantees. ACC 2016: 5716-5721 - [c6]Kin Gwn Lore, Soumik Sarkar, Devesh K. Jha:
Topology control in mobile sensor networks using information space feedback. ACC 2016: 6405-6410 - 2015
- [j1]Devesh K. Jha, Thomas A. Wettergren, Asok Ray, Kushal Mukherjee:
Topology optimisation for energy management in underwater sensor networks. Int. J. Control 88(9): 1775-1788 (2015) - [c5]Yue Li, Devesh K. Jha, Asok Ray, Thomas A. Wettergren:
Feature level sensor fusion for target detection in dynamic environments. ACC 2015: 2433-2438 - [c4]Pritthi Chattopadhyay, Devesh K. Jha, Soumik Sarkar, Asok Ray:
Path planning in GPS-denied environments: A collective intelligence approach. ACC 2015: 3082-3087 - [c3]Devesh K. Jha, Abhishek Srivastav, Kushal Mukherjee, Asok Ray:
Depth estimation in Markov models of time-series data via spectral analysis. ACC 2015: 5812-5817 - [c2]Soumalya Sarkar, Devesh K. Jha, Asok Ray, Yue Li:
Dynamic data-driven symbolic causal modeling for battery performance & health monitoring. FUSION 2015: 1395-1402 - 2013
- [c1]Siddharth Sonti, Nurali Virani, Devesh K. Jha, Kushal Mukherjee, Asok Ray:
Language measure-theoretic path planning in the presence of dynamic obstacles. ACC 2013: 5110-5115
Coauthor Index
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