Keeping Ground Robots on the Move Through Battery & Mission Management
Tulga Ersal, Youngki Kim, John Broderick, Tianyou Guo, Amir Sadrpour, Anna G. Stefanopoulou, Jason B. Siegel, Dawn M. Tilbury, Ella Atkins, Huei Peng, Jionghua Jin, A. Galip Ulsoy
- Year
- 2014
- Citations
- 3
Abstract
This article summarizes a recent collaboration at the University of Michigan's Automotive Research Center that considered best use of batteries in ground robots from several perspectives, such as planning the mission and tracking energy during its execution. The paper illustrates the four main subproblems addressed in this collaboration. Specifically, an area coverage problem is considered using a tracked robot, and the development of an energy-efficient coverage plan is first addressed. Track-terrain interaction is then modeled to better predict the power consumption due to locomotion on different types of terrains. Using a coverage problem as an example, this article shows that managing the battery and the mission properly is critical for ground robots to successfully complete given tasks and make maximum use of their capabilities. To this end, the problems of energy-efficient coverage planning, predicting the locomotion power requirements, controlling the battery power with thermal and electrical constraints, and tracking the mission energy requirements online based on a combination of prior knowledge and real-time data are all tightly connected to each other.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002