51 citations · 117 across the 21 of their papers we have counts for
6 papers · 1 filter
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-…
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…
Capsizing-Guided Trajectory Optimization for Autonomous Navigation with Rough Terrain
Wei Zhang, Yinchuan Wang, Wangtao Lu +4
It is a challenging task for ground robots to autonomously navigate in harsh environments due to the presence of non-trivial obstacles and uneven terrain. This requires trajectory…
Embodied Perception for Test-time Grasping Detection Adaptation with Knowledge Infusion
Jin Liu, Jialong Xie, Leibing Xiao +2
It has always been expected that a robot can be easily deployed to unknown scenarios, accomplishing robotic grasping tasks without human intervention. Nevertheless, existing grasp…
ROLO-SLAM: Rotation-Optimized LiDAR-Only SLAM in Uneven Terrain with Ground Vehicle
Yinchuan Wang, Bin Ren, Xiang Zhang +5
LiDAR-based SLAM is recognized as one effective method to offer localization guidance in rough environments. However, off-the-shelf LiDAR-based SLAM methods suffer from significant…