Walking and Chewing Gum: A Basal Ganglia Vertebrate Robot Under Realistic Contact Physics

We ported EASA (Embedded Action Selection Architecture) [1], based on the basal ganglia model of [2], originally validated on a Khepera I with a gripper in a foraging task, to a modern rigid-body physics engine, with actual geometry extracted from the same hardware's robot definition files. The decision circuitry remained unchanged in its constants. The actual contact physics revealed several behaviors that previous platforms did not demonstrate in the same way, including gripping failures due to an off-center grasp, an arm that could remain indefinitely in a lowered position, and a periodic navigation orbit that avoided the center of the environment. A systematic dopamine sweep showed that the model's original calibration point, 0.2, corresponds to the observed minimum total task failure among five tested levels. We observed a specific mechanism behind a motor distortion effect already described in previous work with the same model: motor activity of behaviors that lose selection competence by filtering into the final robot command. Our results indicate that the effect does not appear to depend on simultaneous channel selection at the thalamic level but rather on a specific threshold at the motor activity combination stage [3]. A preliminary execution mode inspired by the procedure reported for real hardware showed worse performance at all dopamine levels tested, with no classical form of dithering explaining the effect [4]. This work suggests that porting a historical neuro-robotic model to a modern physics engine requires adjustments beyond a simple code translation.