Power-minimization and energy-reduction autonomous navigation of an omnidirectional Mecanum robot via the dynamic window approach local trajectory planning
Li Xie, Christian Henkel, Karl Stol, Wei Xu
- 发表年份
- 2018
- 引用次数
- 44
- 访问权限
- 开放获取
摘要
To improve the energy efficiency of the Mecanum wheel, this article extends the dynamic window approach by adding a new energy-related criterion for minimizing the power consumption of autonomous mobile robots. The energy consumption of the Mecanum robot is first modeled by considering major factors. Then, the model is utilized in the extended dynamic window approach–based local trajectory planner to additionally evaluate the omnidirectional velocities of the robot. Based on the new trajectory planning objective that minimizes power consumption, energy-reduction autonomous navigation is proposed via the combinational cost objectives of low power consumption and high speed. Comprehensive experiments are performed in various autonomous navigation task scenarios, to validate the energy consumption model and to show the effectiveness of the proposed technique in minimizing the power consumption and reducing the energy consumption. It is observed that the technique effectively takes advantage of the Mecanum robot’s redundant maneuverability, can cope with any type of path and is able to fulfil online obstacle avoidance.
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