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IROS
2006
IEEE

Learning to Drive Among Obstacles

9 years 5 months ago
Learning to Drive Among Obstacles
— 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.
Bradley Hamner, Sebastian Scherer, Sanjiv Singh
Added 12 Jun 2010
Updated 12 Jun 2010
Type Conference
Year 2006
Where IROS
Authors Bradley Hamner, Sebastian Scherer, Sanjiv Singh
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