6 citations · 7 across the 13 of their papers we have counts for
14 papers
Learning-Accelerated Narrow-Phase Collision Detection via Check Ordering for Sampling-Based Motion Planning
Hao Jiang, Yinghan Wang, Jianping He +1
Collision detection is critical for ensuring the safety of planned paths. However, it imposes a non-negligible computational burden on motion planners, motivating extensive studies…
BridgeFlow: Fast and Robust SE(2)-Equivariant Motion Planning with Flow Matching
Xinzhe Zhou, Xuyang Wang, Xiaoming Duan +1
In robotic motion planning, equivariance to rigid body transformations is crucial for robust spatial generalization. However, current learning-based planners face a critical dilemm…
Minimizing Worst-Case Weighted Latency for Multi-Robot Persistent Monitoring: Theory and RL-Based Solutions
Weizhen Wang, Ziheng Wang, Jianping He +2
We study multi-robot persistent monitoring on weighted graphs, where node weights encode monitoring priorities and edge weights encode travel distances. The goal is to design joint…
Optimal Unpredictable Control for Linear Systems
Chendi Qu, Jianping He, Jialun Li +1
In this paper, we investigate how to achieve the unpredictability against malicious inferences for linear systems. The key idea is to add stochastic control inputs, named as unpred…
Aucamp: An Underwater Camera-Based Multi-Robot Platform with Low-Cost, Distributed, and Robust Localization
Jisheng Xu, Ding Lin, Pangkit Fong +3
This paper introduces an underwater multi-robot platform, named Aucamp, characterized by cost-effective monocular-camera-based sensing, distributed protocol and robust orientation…
IDEAL: Data Equilibrium Adaptation for Multi-Capability Language Model Alignment
Chenlin Ming, Chendi Qu, Mengzhang Cai +6
Large Language Models (LLMs) have achieved impressive performance through Supervised Fine-tuning (SFT) on diverse instructional datasets. When training on multiple capabilities sim…
Formation Maneuver Control Based on the Augmented Laplacian Method
Xinzhe Zhou, Xuyang Wang, Xiaoming Duan +2
This paper proposes a novel formation maneuver control method for both 2-D and 3-D space, which enables the formation to translate, scale, and rotate with arbitrary orientation. Th…
Analysis of On-policy Policy Gradient Methods under the Distribution Mismatch
Weizhen Wang, Jianping He, Xinzhe Zhou +1
Policy gradient methods are among the most successful approaches for solving challenging reinforcement learning problems. Despite their empirical success, many state-of-the-art pol…
3DIOC: Direct Data-Driven Inverse Optimal Control for LTI Systems
Chendi Qu, Jianping He, Xiaoming Duan
This paper addresses the Direct Data-Driven Inverse Optimal Control (3DIOC) problem for linear time-invariant (LTI) systems under the linear quadratic (LQ) control. Unlike traditio…
Stochastic Trajectory Optimization for Robotic Skill Acquisition From a Suboptimal Demonstration
Chenlin Ming, Zitong Wang, Boxuan Zhang +3
Learning from Demonstration (LfD) has emerged as a crucial method for robots to acquire new skills. However, when given suboptimal task trajectory demonstrations with shape charact…
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…