Use Your Illusion: Sensorimotor Self-simulation Allows Complex Agents to Plan with Incomplete Self-knowledge

摘要

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.