Self-designing resilient robot gaits

http://www.youtube.com/watch?v=rkGaQqkyWII
(thanks to Andrew Murphie for the link)

The robot from Cornell University in this video ‘generates a conception of itself’ and improvises ways of moving around. At startup, the design has been left incomplete, and the robot itself finishes the design. As the robot starts up, it moves all its parts to establish its own morphology. If it has been damaged or reorganised, it can adapt to its new body and still improvise getting around.

Unlike the programmed gaits in the previous Following Robots post, this robot belongs to a tradition of self-generative designs. In the documentation, the developers emphasise that this robot generates internal models — diagrams in the robot’s mind that represent its body. The principle of creating mathematical models of the robotic body (and of the artificially intelligent mind) is the dominant approach to designing self-aware autonomous systems.

Against the internal model approach, an alternative view proposes bottom-up designs, such as in Simon Penny’s work (see his paper ‘Trying to be Calm: Ubiquity, Cognitivism and Embodiment’). This tradition critiques the assumption that robotic movement requires models, and that models explain robotic movement and ‘awareness’.

Watching this mangle of motors, sensors and connections struggle to get to its feet, irrespective of the mathematics of its internal model, the information in play clearly comes from the bottom up. The gait is not calculated in the internal model and then applied to the outside. It is generated in the encounter of robot with the gravity-bound world. The model is a vectoral diagram of the forces at play in the robot body, and the ‘model’ is inseparably part of the world.