Use your illusion: sensorimotor self-simulation allows complex agents to plan with incomplete self-knowledge

Authors:
Richard Vaughan;Mauricio Zuluaga
Affiliations:
Autonomy Lab, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada;Autonomy Lab, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada
Venue:
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
Year:
2006

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Abstract

We present a practical application of sensorimotor self- simulation for a mobile robot Using its self-simulation, the robot can reason about its ability to perform tasks, despite having no model of many of its internal processes and thus no way to create an a priori configuration space in which to search We suggest that this in-the-head rehearsal of tasks is particularly useful when the tasks carry a high risk of robot “death”, as it provides a source of negative feedback in perfect safety This approach is a useful complement to existing work using forward models for anticipatory behaviour A minimal system is shown to be effective in simulation and real-world experiments The virtues and limitations of the approach are discussed and future work suggested.