6 citations · 13 across the 9 of their papers we have counts for
9 papers
Multi-Tree Guided Efficient Robot Motion Planning
Zhirui Sun, Jiankun Wang, Max Q. -H. Meng
Motion Planning is necessary for robots to complete different tasks. Rapidly-exploring Random Tree (RRT) and its variants have been widely used in robot motion planning due to thei…
Learning-based Fast Path Planning in Complex Environments
Jianbang Liu, Baopu Li, Tingguang Li +3
In this paper, we present a novel path planning algorithm to achieve fast path planning in complex environments. Most existing path planning algorithms are difficult to quickly fin…
Hierarchical Policy for Non-prehensile Multi-object Rearrangement with Deep Reinforcement Learning and Monte Carlo Tree Search
Fan Bai, Fei Meng, Jianbang Liu +2
Non-prehensile multi-object rearrangement is a robotic task of planning feasible paths and transferring multiple objects to their predefined target poses without grasping. It needs…
Deep Learning-based Biological Anatomical Landmark Detection in Colonoscopy Videos
Kaiwei Che, Chengwei Ye, Yibing Yao +4
Colonoscopy is a standard imaging tool for visualizing the entire gastrointestinal (GI) tract of patients to capture lesion areas. However, it takes the clinicians excessive time t…
Learning Robot Exploration Strategy with 4D Point-Clouds-like Information as Observations
Zhaoting Li, Tingguang Li, Jiankun Wang +1
Being able to explore unknown environments is a requirement for fully autonomous robots. Many learning-based methods have been proposed to learn an exploration strategy. In the fro…
No Need for Interactions: Robust Model-Based Imitation Learning using Neural ODE
HaoChih Lin, Baopu Li, Xin Zhou +2
Interactions with either environments or expert policies during training are needed for most of the current imitation learning (IL) algorithms. For IL problems with no interactions…