Context Dependant Iterative Parameter Optimisation for Robust Robot Navigation

Binch, Adam, Das, Gautham, Pulido Fentanes, Jaime and Hanheide, Marc (2020) Context Dependant Iterative Parameter Optimisation for Robust Robot Navigation. In: 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, France.

Full content URL: https://doi.org/10.1109/ICRA40945.2020.9196550

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Context Dependant Iterative Parameter Optimisation for Robust Robot Navigation
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Abstract

Progress in autonomous mobile robotics has seen significant advances in the development of many algorithms for motion control and path planning. However, robust performance from these algorithms can often only be expected if the parameters controlling them are tuned specifically for the respective robot model, and optimised for specific scenarios in the environment the robot is working in. Such parameter tuning can, depending on the underlying algorithm, amount to a substantial combinatorial challenge, often rendering extensive manual tuning of these parameters intractable. In this paper, we present a framework that permits the use of different navigation actions and/or parameters depending on the spatial context of the navigation task, while considering the respective navigation algorithms themselves mostly as a "black box", and find suitable parameters by means of an iterative optimisation, improving for performance metrics in simulated environments. We present a genetic algorithm incorporated into the framework and empirically show that the resulting parameter sets lead to substantial performance improvements in both simulated and real-world environments in the domain of agricultural robots.

Keywords:robot navigation, genetic algorithms, Parameter tuning
Subjects:H Engineering > H670 Robotics and Cybernetics
H Engineering > H671 Robotics
Divisions:College of Science > Lincoln Institute for Agri-Food Technology
ID Code:42389
Deposited On:30 Sep 2020 13:17

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