The navigation for home service robot with the least power consumption
Yupei Yan
TL;DR
This paper presents a new navigation system for home robots that uses the least amount of power by optimizing localization, path planning, and obstacle avoidance.
Contribution
The paper introduces five novel methods to reduce power consumption in robot navigation, including optimized localization and path planning techniques.
Findings
Straight paths and in-place rotations consume less power than curved paths.
Machine learning improves angle localization with minimal power use.
The proposed algorithm outperforms DWA and TEB in power efficiency during navigation.
Abstract
This paper discusses the navigation of the home service robot with least power consumption. Firstly, the localization of position of the robot with least power consumption is analyzed based on the geometrical relationship between robot and home appliance, then the localization of angle of the robot in the indoor environment with least power is proposed, which can be predicted by machine learning algorithms. Following, the path planning of the robot with least power is proposed, two supplements and optimizations of previous algorithms are proposed, the power consumption on the moving path is calculated according to the law of energy conservation, the conclusion is obtained that moving straight path and rotating in place will save more power than moving curve path. Then, the obstacle avoidance of the robot in the dynamic environment with least power consumption is proposed, the navigation…
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Taxonomy
TopicsRobotic Path Planning Algorithms · Robotics and Sensor-Based Localization · Control and Dynamics of Mobile Robots