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Learning to Drive Among Obstacles

Bradley Hamner, Sebastian Scherer and Sanjiv Singh
Conference Paper, Proceedings of 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2663 - 2669, October, 2006

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Abstract– This paper reports on an outdoor mobile robot that learns to avoid collisions by observing a human driver operate a vehicle equipped with sensors that continuously produce a map of the local environment. We have implemented steering control that models human behavior in trying to avoid obstacles while trying to follow a desired path. Here we present the formulation for this control system and its independent parameters, and then show how these parameters can be automatically estimated by observation of a human driver. We present results from experiments with a vehicle (both real and simulated) that avoids obstacles while following a prescribed path at speeds up to 4 m/sec. We compare the proposed method with another method based on Principal Component Analysis, a commonly used learning technique. We find that the proposed method generalizes well and is capable of learning from a small number of examples.

author = {Bradley Hamner and Sebastian Scherer and Sanjiv Singh},
title = {Learning to Drive Among Obstacles},
booktitle = {Proceedings of 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2006},
month = {October},
pages = {2663 - 2669},
} 2017-09-13T10:42:31-04:00