Robot Trajectories Comparison: A Statistical Approach
Ander Ansuategui, Andoni Arruti, Loreto Susperregi, Y. Yurramendi, E. Jauregi, Elena Lazkano, Basilio Sierra
- 发表年份
- 2014
- 引用次数
- 2
- 访问权限
- 开放获取
摘要
The task of planning a collision-free trajectory from a start to a goal position is fundamental for an autonomous mobile robot. Although path planning has been extensively investigated since the beginning of robotics, there is no agreement on how to measure the performance of a motion algorithm. This paper presents a new approach to perform robot trajectories comparison that could be applied to any kind of trajectories and in both simulated and real environments. Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them. Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided. The proposed method has been applied, as an example, to compare two different motion planners, FM(2) and WaveFront, using different environments, robots, and local planners.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991