6 citations · 7 across the 17 of their papers we have counts for
6 papers · 1 filter
Observation-based Optimal Control Law Learning with LQR Reconstruction
Chendi Qu, Jianping He, Xiaoming Duan
Designing controllers to generate various trajectories has been studied for years, while recently, recovering an optimal controller from trajectories receives increasing attention.…
Model Selection for Inverse Reinforcement Learning via Structural Risk Minimization
Chendi Qu, Jianping He, Xiaoming Duan +1
Inverse reinforcement learning (IRL) usually assumes the reward function model is pre-specified as a weighted sum of features and estimates the weighting parameters only. However,…
HiCRISP: An LLM-based Hierarchical Closed-Loop Robotic Intelligent Self-Correction Planner
Chenlin Ming, Jiacheng Lin, Pangkit Fong +3
The integration of Large Language Models (LLMs) into robotics has revolutionized human-robot interactions and autonomous task planning. However, these systems are often unable to s…
Affordance-Driven Next-Best-View Planning for Robotic Grasping
Xuechao Zhang, Dong Wang, Sun Han +7
Grasping occluded objects in cluttered environments is an essential component in complex robotic manipulation tasks. In this paper, we introduce an AffordanCE-driven Next-Best-View…
Control Input Inference of Mobile Agents under Unknown Objective
Chendi Qu, Jianping He, Xiaoming Duan +1
Trajectory and control secrecy is an important issue in robotics security. This paper proposes a novel algorithm for the control input inference of a mobile agent without knowing i…
Revisiting Estimation Bias in Policy Gradients for Deep Reinforcement Learning
Haoxuan Pan, Deheng Ye, Xiaoming Duan +4
We revisit the estimation bias in policy gradients for the discounted episodic Markov decision process (MDP) from Deep Reinforcement Learning (DRL) perspective. The objective is fo…