On the Role of Stored Internal State in the Control of Autonomous Mobile Robots

This article informally examines the role of stored internal state (that is, memory) in the control of autonomous mobile robots. The difficulties associated with using stored internal state are reviewed. It is argued that the underlying cause of these problems is the implicit predictions contained within the state, and, therefore, many of the problems can be solved by taking care that the internal state contains information only about predictable aspects of the environment. This architecture was successfully used to control real-world and simulated real-world autonomous mobile robots performing complex navigation tasks.