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20232026
most citedMotion Planning for Robotics: A Review for Sampling-based Planners

51 citations · 87 across the 22 of their papers we have counts for

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Showing 2025Show all

12 papers · 1 filter

cs.RO2025

Tele-rehabilitation with online skill transfer and adaptation in

Tianle Ni, Xiao Chen, Hamid Sadeghian +1

This paper proposes a tele-teaching framework for the domain of robot-assisted tele-rehabilitation. The system connects two robotic manipulators on therapist and patient side via b…

eess.SY2025★ 1 cited

Learning a Shape-adaptive Assist-as-needed Rehabilitation Policy from Therapist-informed Input

Zhimin Hou, Jiacheng Hou, Xiao Chen +3

Therapist-in-the-loop robotic rehabilitation has shown great promise in enhancing rehabilitation outcomes by integrating the strengths of therapists and robotic systems. However, i…

cs.RO2025

Video-to-BT: Generating Reactive Behavior Trees from Human Demonstration Videos for Robotic Assembly

Xiwei Zhao, Yiwei Wang, Yansong Wu +5

Modern manufacturing demands robotic assembly systems with enhanced flexibility and reliability. However, traditional approaches often rely on programming tailored to each product…

cs.RO2025

Prompt2Auto: From Motion Prompt to Automated Control via Geometry-Invariant One-Shot Gaussian Process Learning

Zewen Yang, Xiaobing Dai, Dongfa Zhang +5

Learning from demonstration allows robots to acquire complex skills from human demonstrations, but conventional approaches often require large datasets and fail to generalize acros…

cs.RO2025

RCM Constraint-Consistent Dynamic Control in Surgical Robots

Yu Li, Hamid Sadeghian, Zewen Yang +2

Robotic-assisted minimally invasive surgery (RAMIS) requires accurate enforcement of the remote center of motion (RCM) constraint to ensure safe tool motion through a trocar. Exist…

cs.RO2025★ 2 cited

APT*: Asymptotically Optimal Motion Planning via Adaptively Prolated Elliptical R-Nearest Neighbors

Liding Zhang, Sicheng Wang, Kuanqi Cai +5

Optimal path planning aims to determine a sequence of states from a start to a goal while accounting for planning objectives. Popular methods often integrate fixed batch sizes and…

cs.RO2025★ 7 cited

Tree-Based Grafting Approach for Bidirectional Motion Planning with Local Subsets Optimization

Liding Zhang, Yao Ling, Zhenshan Bing +3

Bidirectional motion planning often reduces planning time compared to its unidirectional counterparts. It requires connecting the forward and reverse search trees to form a continu…

cs.RO2025★ 10 cited

Elliptical K-Nearest Neighbors -- Path Optimization via Coulomb's Law and Invalid Vertices in C-space Obstacles

Liding Zhang, Zhenshan Bing, Yu Zhang +5

Path planning has long been an important and active research area in robotics. To address challenges in high-dimensional motion planning, this study introduces the Force Direction…

cs.RO2025

Direction Informed Trees (DIT*): Optimal Path Planning via Direction Filter and Direction Cost Heuristic

Liding Zhang, Kejia Chen, Kuanqi Cai +7

Optimal path planning requires finding a series of feasible states from the starting point to the goal to optimize objectives. Popular path planning algorithms, such as Effort Info…

cs.LG2025

Streaming Generated Gaussian Process Experts for Online Learning and Control: Extended Version

Zewen Yang, Dongfa Zhang, Xiaobing Dai +5

Gaussian Processes (GPs), as a nonparametric learning method, offer flexible modeling capabilities and calibrated uncertainty quantification for function approximations. Additional…

cs.RO2025

SafeFlow: Safe Robot Motion Planning with Flow Matching via Control Barrier Functions

Xiaobing Dai, Zewen Yang, Dian Yu +4

Recent advances in generative modeling have led to promising results in robot motion planning, particularly through diffusion and flow matching (FM)-based models that capture compl…

cs.RO2025

SharedAssembly: A Data Collection Approach via Shared Tele-Assembly

Yansong Wu, Xiao Chen, Yu Chen +4

High-precision, tight-clearance assembly demonstrations are indispensable for training tactile-aware robotic foundation models, yet their acquisition is heavily bottlenecked by the…