Behavioural cloning for driving robots over rough terrain
MetadataShow full item record
Controllers for autonomous mobile robots that operate in rough terrain must consider the shape of the surrounding terrain and its impact on the robot's movements. For complex terrain, these interactions are extremely difficult to model in a way that allows traditional controllers to be built. We have used Behavioural Cloning, a type of learning by imitation that produces rules that clone the skills of an expert human operator. We have also developed an autonomous instructor in simulation and used it to generate training data from which we have cloned controllers. The resulting controllers perform at a level comparable to that of a human expert. The controllers behave similarly both in simulation, where they were developed, and on the physical robot without the need for further modification or training.
Showing items related by title, author, creator and subject.
Cui, Lei; Cheong, P.; Adams, Ridge; Johnson, T. (2014)This paper describes the AmBot, a centipede-inspired amphibious robot for monitoring the Swan-Canning River, the most important estuary system in Western Australia. The major challenge in developing such a robot lies in ...
Mann, G.; Small, N.; Lee, K.; Clarke, J.; Sheh, Raymond (2015)Controlled testing on standard tasks and within standard environments can provide meaningful performance comparisons between robots of heterogeneous design. But because they must perform practical tasks in unstructured, ...
Weber, Keven (1998)Giving robots the ability to move around autonomously in various real-world environments has long been a major challenge for Artificial Intelligence. New approaches to the design and control of autonomous robots have shown ...