Devesh K. Jha

Orcid: 0000-0002-7843-9545

According to our database1, Devesh K. Jha authored at least 74 papers between 2013 and 2024.

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Bibliography

2024
Robust In-Hand Manipulation with Extrinsic Contacts.
CoRR, 2024

iPolicy: Incremental Policy Algorithms for Feedback Motion Planning.
CoRR, 2024

2023
L$^{3}$ F-TOUCH: A Wireless GelSight With Decoupled Tactile and Three-Axis Force Sensing.
IEEE Robotics Autom. Lett., 2023

Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection.
CoRR, 2023

Interactive Planning Using Large Language Models for Partially Observable Robotics Tasks.
CoRR, 2023

Tactile Estimation of Extrinsic Contact Patch for Stable Placement.
CoRR, 2023

Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos.
CoRR, 2023

A Virtual Reality Teleoperation Interface for Industrial Robot Manipulators.
CoRR, 2023

Robust Pivoting Manipulation using Contact Implicit Bilevel Optimization.
CoRR, 2023

Simultaneous Trajectory Optimization and Contact Selection for Multi-Modal Manipulation Planning.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Tactile-Filter: Interactive Tactile Perception for Part Mating.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Constrained Dynamic Movement Primitives for Collision Avoidance in Novel Environments.
IROS, 2023

Tactile Tool Manipulation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Covariance Steering for Uncertain Contact-rich Systems.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Simultaneous Tactile Estimation and Control of Extrinsic Contact.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Design of Adaptive Compliance Controllers for Safe Robotic Assembly.
Proceedings of the European Control Conference, 2023

Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control.
Proceedings of the European Control Conference, 2023

Chance-Constrained Optimization in Contact-rich Systems.
Proceedings of the American Control Conference, 2023

2022
Constrained Dynamic Movement Primitives for Safe Learning of Motor Skills.
CoRR, 2022

Learning robot motor skills with mixed reality.
CoRR, 2022

Chance-Constrained Optimization in Contact-Rich Systems for Robust Manipulation.
CoRR, 2022

Active Exploration for Robotic Manipulation.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Robust Pivoting: Exploiting Frictional Stability Using Bilevel Optimization.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

PyROBOCOP: Python-based Robotic Control & Optimization Package for Manipulation.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Imitation and Supervised Learning of Compliance for Robotic Assembly.
Proceedings of the European Control Conference, 2022

Homogeneous Infeasible Interior Point Method for Convex Quadratic Programs.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021
Safe Approximate Dynamic Programming via Kernelized Lipschitz Estimation.
IEEE Trans. Neural Networks Learn. Syst., 2021

Data-Efficient Learning for Complex and Real-Time Physical Problem Solving Using Augmented Simulation.
IEEE Robotics Autom. Lett., 2021

PYROBOCOP : Python-based Robotic Control & Optimization Package for Manipulation and Collision Avoidance.
CoRR, 2021

Distributed Task Allocation in Homogeneous Swarms Using Language Measure Theory.
CoRR, 2021

Markov Modeling of Time-Series Data using Symbolic Analysis.
CoRR, 2021

Training Larger Networks for Deep Reinforcement Learning.
CoRR, 2021

Trajectory Optimization for Manipulation of Deformable Objects: Assembly of Belt Drive Units.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020
Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements.
IEEE Robotics Autom. Lett., 2020

Towards Human-Level Learning of Complex Physical Puzzles.
CoRR, 2020

Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks.
CoRR, 2020

Multi-label Prediction in Time Series Data using Deep Neural Networks.
CoRR, 2020

Generative Deep Learning Model for a Multi-Level Nano-Optic Broadband Power Splitter.
Proceedings of the Optical Fiber Communications Conference and Exhibition, 2020

Deep Neural Networks for Designing Integrated Photonics.
Proceedings of the Optical Fiber Communications Conference and Exhibition, 2020

CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Local Policy Optimization for Trajectory-Centric Reinforcement Learning.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
Proceedings of the 37th International Conference on Machine Learning, 2020

Deep Reactive Planning in Dynamic Environments.
Proceedings of the 4th Conference on Robot Learning, 2020

2019
Sequential hypothesis tests for streaming data via symbolic time-series analysis.
Eng. Appl. Artif. Intell., 2019

Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control.
CoRR, 2019

Deep Neural Network Inverse Modeling for Integrated Photonics.
Proceedings of the Optical Fiber Communications Conference and Exhibition, 2019

Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze.
Proceedings of the International Conference on Robotics and Automation, 2019

Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics.
Proceedings of the International Conference on Robotics and Automation, 2019

Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function.
Proceedings of the 36th International Conference on Machine Learning, 2019

Anomaly Detection for Insertion Tasks in Robotic Assembly Using Gaussian Process Models.
Proceedings of the 17th European Control Conference, 2019

Quasi-Newton Trust Region Policy Optimization.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Data-Driven Control Policies for Partially Known Systems via Kernelized Lipschitz Learning.
Proceedings of the 2019 American Control Conference, 2019

2018
Markov Modeling of Time Series via Spectral Analysis for Detection of Combustion Instabilities.
Proceedings of the Handbook of Dynamic Data Driven Applications Systems., 2018

Information-Theoretic Performance Analysis of Sensor Networks via Markov Modeling of Time Series Data.
IEEE Trans. Cybern., 2018

Symbolic analysis-based reduced order Markov modeling of time series data.
Signal Process., 2018

Algorithms for Task Allocation in Homogeneous Swarm of Robots.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

2017
Information Fusion of Passive Sensors for Detection of Moving Targets in Dynamic Environments.
IEEE Trans. Cybern., 2017

Learning to regulate rolling ball motion.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

A two-stage RRT path planner for automated parking.
Proceedings of the 13th IEEE Conference on Automation Science and Engineering, 2017

2016
Path planning in GPS-denied environments via collective intelligence of distributed sensor networks.
Int. J. Control, 2016

Data-driven robot gait modeling via symbolic time series analysis.
Proceedings of the 2016 American Control Conference, 2016

Multimodal spatiotemporal information fusion using neural-symbolic modeling for early detection of combustion instabilities.
Proceedings of the 2016 American Control Conference, 2016

Topology control in mobile sensor networks using information space feedback.
Proceedings of the 2016 American Control Conference, 2016

Sensor selection for passive sensor networks in dynamic environment: A dynamic data-driven approach.
Proceedings of the 2016 American Control Conference, 2016

Data-driven anytime algorithms for motion planning with safety guarantees.
Proceedings of the 2016 American Control Conference, 2016

2015
Topology optimisation for energy management in underwater sensor networks.
Int. J. Control, 2015

Dynamic data-driven symbolic causal modeling for battery performance & health monitoring.
Proceedings of the 18th International Conference on Information Fusion, 2015

Feature level sensor fusion for target detection in dynamic environments.
Proceedings of the American Control Conference, 2015

Depth estimation in Markov models of time-series data via spectral analysis.
Proceedings of the American Control Conference, 2015

Path planning in GPS-denied environments: A collective intelligence approach.
Proceedings of the American Control Conference, 2015

2013
Language measure-theoretic path planning in the presence of dynamic obstacles.
Proceedings of the American Control Conference, 2013


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