From Adaptive Locomotion to Predictive Action Selection – Cognitive Control for a Six-Legged Walker

Schilling, Malte; Paskarbeit, J.; Ritter, H.; Schneider, A.; Cruse, H.

Forschungsartikel (Zeitschrift) | Peer reviewed

Zusammenfassung

Locomotion in animals provides a model for adaptive behavior as it is able to deal with various kinds of perturbations. Work in insects suggests that this evolved flexibility results from a modular architecture, which can be characterized by a recurrent neural network allowing for various emerging attractor states. Whereas a lower control-level coordinates joint movements on a short timescale, a higher-level handles action selection on longer timescales. Implementation of such a control system on a walking hexapod robot was able to deal with various walking patterns including disturbances such as uneven terrain or loss of a leg. Here, we propose a cognitive expansion to the adaptive control system that allows dealing with novel challenging situations. This approach makes use of an internal simulation-based planner that is triggered when the model-free controller fails to recover from an unstable pose. Using a grounded internal body model, the planner then tries, in internal simulation, different solutions out of context, and thus, proposes a new plan to be executed on the real robot. We demonstrate the feasibility of this control approach for walking over terrain with uncertain footholds in three scenarios.

Details zur Publikation

FachzeitschriftIEEE Transactions on Robotics
Jahrgang / Bandnr. / Volume38
Ausgabe / Heftnr. / Issue2
Seitenbereich666-682
StatusVeröffentlicht
Veröffentlichungsjahr2022
DOI10.1109/TRO.2021.3106832
Link zum Volltexthttps://doi.org/10.1109/TRO.2021.3106832
Stichwörterrobotics; cognitive control; locomotion

Autor*innen der Universität Münster

Schilling, Malte
Professur für Praktische Informatik (Prof. Schilling)