Kick control: using the attracting states arising within the sensorimotor loop of self-organized robots as motor primitives
Bulcs\'u S\'andor, Michael Nowak, Tim Koglin, Laura Martin and, Claudius Gros

TL;DR
This paper explores how self-organized robots develop attractor states in their sensorimotor loops and demonstrates how small control inputs can switch the robot between different locomotion modes by leveraging these attractors.
Contribution
It introduces the concept of kick control to manipulate attractor states in self-organized robots, enabling robust transitions between locomotion behaviors using simple control commands.
Findings
Self-organized attractor landscape can be morphed by control signals and environment interactions.
Bumping into obstacles can switch the robot's motion direction autonomously.
Sensorimotor states serve as highly compliant motor primitives.
Abstract
Self-organized robots may develop attracting states within the sensorimotor loop, that is within the phase space of neural activity, body, and environmental variables. Fixpoints, limit cycles, and chaotic attractors correspond in this setting to a non-moving robot, to directed, and to irregular locomotion respectively. Short higher-order control commands may hence be used to kick the system from one self-organized attractor robustly into the basin of attraction of a different attractor, a concept termed here as kick control. The individual sensorimotor states serve in this context as highly compliant motor primitives. We study different implementations of kick control for the case of simulated and real-world wheeled robots, for which the dynamics of the distinct wheels is generated independently by local feedback loops. The feedback loops are mediated by rate-encoding neurons…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
