8 citations · 11 across the 6 of their papers we have counts for
6 papers
Ego-Motion Aware Target Prediction Module for Robust Multi-Object Tracking
Navid Mahdian, Mohammad Jani, Amir M. Soufi Enayati +1
Multi-object tracking (MOT) is a prominent task in computer vision with application in autonomous driving, responsible for the simultaneous tracking of multiple object trajectories…
Extended Reality for Enhanced Human-Robot Collaboration: a Human-in-the-Loop Approach
Yehor Karpichev, Todd Charter, Jayden Hong +4
The rise of automation has provided an opportunity to achieve higher efficiency in manufacturing processes, yet it often compromises the flexibility required to promptly respond to…
Using Implicit Behavior Cloning and Dynamic Movement Primitive to Facilitate Reinforcement Learning for Robot Motion Planning
Zengjie Zhang, Jayden Hong, Amir Soufi Enayati +1
Reinforcement learning (RL) for motion planning of multi-degree-of-freedom robots still suffers from low efficiency in terms of slow training speed and poor generalizability. In th…
Human-Robot Skill Transfer with Enhanced Compliance via Dynamic Movement Primitives
Jayden Hong, Zengjie Zhang, Amir M. Soufi Enayati +1
Finding an efficient way to adapt robot trajectory is a priority to improve overall performance of robots. One approach for trajectory planning is through transferring human-like s…
Facilitating Sim-to-real by Intrinsic Stochasticity of Real-Time Simulation in Reinforcement Learning for Robot Manipulation
Ram Dershan, Amir M. Soufi Enayati, Zengjie Zhang +2
Simulation is essential to reinforcement learning (RL) before implementation in the real world, especially for safety-critical applications like robot manipulation. Conventionally,…
Sample-Efficient Reinforcement Learning with Symmetry-Guided Demonstrations for Robotic Manipulation
Amir M. Soufi Enayati, Zengjie Zhang, Kashish Gupta +1
Reinforcement learning (RL) suffers from low sample efficiency, particularly in high-dimensional continuous state-action spaces of complex robotic manipulation tasks. RL performanc…