Mobile robots contributed significantly to the intelligent development of human society, and
the motion-planning policy is critical for mobile robots. This paper reviews the methods …

随着移动机器人作业环境复杂度的提高, 随机性的增强, 信息量的减少, 移动机器人的运动规划
能力受到了严峻的挑战. 研究移动机器人高效自主的运动规划理论与方法 …

Reinforcement Learning (RL), bolstered by the expressive capabilities of Deep Neural
Networks (DNNs) for function approximation, has demonstrated considerable success in …

As one of the most promising areas, mobile robots draw much attention these years. Current
work in this field is often evaluated in a few manually designed scenarios, due to the lack of …

Autonomous elevator button operation is an indispensable function for robot-elevator
interaction, which has long been considered an intelligent solution for multifloor navigation …

This paper presents the first active object mapping framework for complex robotic
manipulation and autonomous perception tasks. The framework is built on an object SLAM …

Reinforcement Learning (RL), bolstered by the expressive capabilities of Deep Neural
Networks (DNNs) for function approximation, has demonstrated considerable success in …

This paper presents a fundamental algorithm, called VDB-EDT, for Euclidean distance
transform (EDT) based on the VDB data structure. The algorithm executes on grid maps and …

This paper presents a search-based partial motion planner for generating feasible
trajectories of car-like robots in highly dynamic environments. The planner searches for …

We present a learning-based approach to solving a Rubik's cube with a multi-fingered
dexterous hand. Despite the promising performance of dexterous in-hand manipulation …