Possessing the merits of high efficiency, low consumption, and versatility, emerging photonic
memristive and memristive‐like devices exhibit an attractive future in constructing novel …

A fundamental task in robotics is to plan collision‐free motions among a set of obstacles.
Recently, learning‐based motion‐planning methods have shown significant advantages in …

In this paper, we present a novel path planning algorithm called Kinematic Constrained Bi-
directional Rapidly-exploring Random Tree with Efficient Branch Pruning (KB-RRT*), which …

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 …

We propose and experimentally demonstrate a reactive planning system for bipedal robots
on unexplored, challenging terrain. The system includes: a multilayer local map for …

For path planning problems based on Rapidly exploring Random Trees (RRT), most new
nodes merely explore the environment unless they are sampled directly from the subset that …

In a large-scale oceanic environment with spatially variable ocean currents, it is vital for
unmanned surface vehicles (USVs) to navigate with a safe and energy-efficient path. In this …

Abstract Autonomous Forklifts (AFs) play a vital role in smart factories, particularly in the
transportation of heavy loads. However, their energy consumption poses a significant …

Autonomous flying vehicles (AFVs) are promising future vehicles, which have high obstacle
avoidance ability. To plan a feasible path in a wide range of cross-country environments for …

Local planning is one of the key technologies for mobile robots to achieve full autonomy and
has been widely investigated. To evaluate mobile robot local planning approaches in a …