10 citations · 25 across the 6 of their papers we have counts for
6 papers
Imitation-Guided Bimanual Planning for Stable Manipulation under Changing External Forces
Kuanqi Cai, Chunfeng Wang, Zeqi Li +5
Robotic manipulation in dynamic environments often requires seamless transitions between different grasp types to maintain stability and efficiency. However, achieving smooth and a…
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-…
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…
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…
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…
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…