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Metrics for performance benchmarking of multi-robot exploration

Zhi Yan, Luc Fabresse, Jannik Laval, Noury Bouraqadi

Year
2015
Citations
41

Abstract

Performance benchmarking has become an important topic within robotics. It is indeed, a critical way to compare different solutions under different conditions. In this paper, we focus on performance benchmarking of multi-robot systems which explore and map unknown terrains. We present a collection of metrics to objectively compare different algorithms that can be applied to collaborative multi-robot exploration. We also identify parameters that impact robotic fleet performances. By varying the parameters, we can identify strengths and limits of an algorithm. This work is also a first concrete step to address the general problem of objectively comparing different multi-robot coordination algorithms. We illustrate these contributions with realistic simulations of the frontier-based exploration strategy. The simulations were implemented in ROS, which enables to uncouple the control software from the drivers of the robot body. We can therefore use the same code on both simulation and real robots.

Keywords

BenchmarkingComputer scienceRobotRoboticsArtificial intelligenceFocus (optics)SoftwareTerrainRobot kinematicsBenchmark (surveying)

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