Kinematic Constraints Based Bi-Directional Rrt (Kb-Rrt) With Parameterized Trajectories For Robot Path Planning In Cluttered Environment

2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)(2019)

引用 36|浏览21
暂无评分
摘要
Optimal path planning and smooth trajectory planning are critical for effective navigation of mobile robots working towards accomplishing complex missions. For autonomous, real time and extended operations of mobile robots, the navigation capability needs to be executed at the edge. Thus, efficient compute, minimum memory utilization and smooth trajectory are the key parameters that drive the successful operation of autonomous mobile robots. Traditionally, navigation solutions focus on developing robust path planning algorithms which are complex and compute/memory intensive. Bidirectional-RRT(Bi-RRT) based path planning algorithms have gained increased attention due to their effectiveness and computational efficiency in generating feasible paths. However, these algorithms neither optimize memory nor guarantee smooth trajectories. To this end, we propose a kinematically constrained Bi-RRT (KB-RRT) algorithm, which restricts the number of nodes generated without compromising on the accuracy and incorporates kinodynamic constraints for generating smooth trajectories, together resulting in efficient navigation of autonomous mobile robots. The proposed algorithm is tested in a highly cluttered environment on an Ackermannsteering vehicle model with severe kinematic constraints. The experimental results demonstrate that KB-RRT achieves three times (3X) better performance in terms of convergence rate and memory utilization compared to a standard Bi-RRT algorithm.
更多
查看译文
关键词
Bi-RRT algorithm,parameterized trajectories,robot path planning,complex missions,navigation capability,autonomous mobile robots,robust path planning algorithms,bidirectional-RRT,kinodynamic constraints,bidirectional RRT,trajectory planning,memory utilization,kinematic constraints,KB-RRT algorithm
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要