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

51 citations · 96 across the 19 of their papers we have counts for

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Showing 2025Show all

11 papers · 1 filter

cs.RO2025

M4Diffuser: Multi-View Diffusion Policy with Manipulability-Aware Control for Robust Mobile Manipulation

Ju Dong, Lei Zhang, Liding Zhang +8

Mobile manipulation requires the coordinated control of a mobile base and a robotic arm while simultaneously perceiving both global scene context and fine-grained object details. E…

cs.RO2025★ 9 cited

Estimated Informed Anytime Search for Sampling-Based Planning via Adaptive Sampler

Liding Zhang, Kuanqi Cai, Yu Zhang +5

Path planning in robotics often involves solving continuously valued, high-dimensional problems. Popular informed approaches include graph-based searches, such as A*, and sampling-…

cs.RO2025

Language-Enhanced Mobile Manipulation for Efficient Object Search in Indoor Environments

Liding Zhang, Zeqi Li, Kuanqi Cai +3

Enabling robots to efficiently search for and identify objects in complex, unstructured environments is critical for diverse applications ranging from household assistance to indus…

cs.RO2025

Deep Fuzzy Optimization for Batch-Size and Nearest Neighbors in Optimal Robot Motion Planning

Liding Zhang, Qiyang Zong, Yu Zhang +2

Efficient motion planning algorithms are essential in robotics. Optimizing essential parameters, such as batch size and nearest neighbor selection in sampling-based methods, can en…

cs.RO2025★ 4 cited

Genetic Informed Trees (GIT*): Path Planning via Reinforced Genetic Programming Heuristics

Liding Zhang, Kuanqi Cai, Zhenshan Bing +2

Optimal path planning involves finding a feasible state sequence between a start and a goal that optimizes an objective. This process relies on heuristic functions to guide the sea…

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.RO2025

Whisker-based Active Tactile Perception for Contour Reconstruction

Yixuan Dang, Qinyang Xu, Yu Zhang +5

Perception using whisker-inspired tactile sensors currently faces a major challenge: the lack of active control in robots based on direct contact information from the whisker. To a…

cs.RO2025

Robotic Long-Horizon Manipulation with Bayesian Non-parametric Skill Priors

Yuan Meng, Xiangtong Yao, Kejia Chen +5

Long-horizon manipulation under sparse rewards remains challenging for reinforcement learning due to delayed feedback and inefficient exploration. Existing skill-based approaches o…