9 citations · 36 across the 11 of their papers we have counts for
9 papers · 1 filter
Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control
Devesh K. Jha, Siddarth Jain, Diego Romeres +2
Robots have been steadily increasing their presence in our daily lives, where they can work along with humans to provide assistance in various tasks on industry floors, in offices,…
Constrained Dynamic Movement Primitives for Safe Learning of Motor Skills
Seiji Shaw, Devesh K. Jha, Arvind Raghunathan +4
Dynamic movement primitives are widely used for learning skills which can be demonstrated to a robot by a skilled human or controller. While their generalization capabilities and s…
Design of Adaptive Compliance Controllers for Safe Robotic Assembly
Devesh K. Jha, Diego Romeres, Siddarth Jain +2
Insertion operations are a critical element of most robotic assembly operation, and peg-in-hole (PiH) insertion is one of the most widely studied tasks in the industrial and academ…
Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry
Siyuan Dong, Devesh K. Jha, Diego Romeres +3
Object insertion is a classic contact-rich manipulation task. The task remains challenging, especially when considering general objects of unknown geometry, which significantly lim…
Model-based Policy Search for Partially Measurable Systems
Fabio Amadio, Alberto Dalla Libera, Ruggero Carli +2
In this paper, we propose a Model-Based Reinforcement Learning (MBRL) algorithm for Partially Measurable Systems (PMS), i.e., systems where the state can not be directly measured,…
Deep Reactive Planning in Dynamic Environments
Kei Ota, Devesh K. Jha, Tadashi Onishi +5
The main novelty of the proposed approach is that it allows a robot to learn an end-to-end policy which can adapt to changes in the environment during execution. While goal conditi…