POA: Passable Obstacles Aware Path-planning Algorithm for Navigation of a Two-wheeled Robot in Highly Cluttered Environments
Alexander Petrovsky, Yomna Youssef, Kirill Myasoedov, Artem Timoshenko, Vladimir Guneavoi, Ivan Kalinov, Dzmitry Tsetserukou
- 发表年份
- 2023
- 访问权限
- 开放获取
摘要
This paper focuses on Passable Obstacles Aware (POA) planner - a novel navigation method for two-wheeled robots in a highly cluttered environment. The navigation algorithm detects and classifies objects to distinguish two types of obstacles - passable and unpassable. Our algorithm allows two-wheeled robots to find a path through passable obstacles. Such a solution helps the robot working in areas inaccessible to standard path planners and find optimal trajectories in scenarios with a high number of objects in the robot's vicinity. The POA planner can be embedded into other planning algorithms and enables them to build a path through obstacles. Our method decreases path length and the total travel time to the final destination up to 43% and 39%, respectively, comparing to standard path planners such as GVD, A*, and RRT*
关键词
相关论文
一种面向线弧增材制造的电动汽车结构可制造性拓扑优化的双环框架
Qiang Cui, Chuan Yu, Daoqian Yang 等 5 位作者
Robotics and Computer-Integrated Manufacturing · 2026
几何数字孪生:一种用于航空发动机装配精度预测的数字智能模型
Ke Shang, Xin Jin, Teli Xu 等 7 位作者
Robotics and Computer-Integrated Manufacturing · 2026
通过人工智能驱动的机器人技术革新产业
Aryan Chaudhary
Recent Advances in Computer Science and Communications · 2026
新型大口径偏置馈电可展开天线设计与动态性能预测
Chuang Shi, Tianming Liu, Ning Xue 等 9 位作者
Aerospace Science and Technology · 2026