In this article, a novel global path planning approach with rapid convergence properties for
autonomous ground vehicles (AGVs) named neural sampling rapidly exploring random tree …

Multispectral object detection has achieved remarkable results due to its ability to fuse
information from visible and thermal modalities in recent years. However, the existing visible …

Recent advances in path-planning algorithms have transformed robotics. The Rapidly
exploring Random Tree (RRT) algorithm underpins autonomous robot navigation. This …

轨迹规划是车载自动泊车系统中的重要功能, 而现有的泊车轨迹规划算法无法兼顾算法泛化性,
计算精度, 求解时效性以及结果最优性. 现采用基于数值优化的轨迹规划技术路线 …

The study presents an optimized Unmanned Surface Vehicle (USV) collision avoidance
decision-making strategy in restricted waters based on the improved Proximal Policy …

Autonomous exploration in unknown environments is an essential capability for mobile
robots. The complexity of autonomous exploration, however, means that existing algorithms …

The robotic autonomous luggage trolley collection system employs robots to gather and
transport scattered luggage trolleys at airports. However, existing methods for detecting and …

This paper introduces SHANGUS, an advanced framework combining Deep Reinforcement
Learning (DRL) with heuristic optimization to improve frontier-based exploration efficiency in …

Trajectory planning is a vital function in vehicular automatic parking systems. Existing
algorithms for automatic parking trajectory planning fail to balance generalizability …