Adaptive locomotion control of hexapod walking robot for traversing rough terrains with position feedback only

Traversing rough terrains is one of the domains where multi-legged walking robots benefit from their relatively more complex kinematics in comparison to wheeled robots. The complexity of walking robots is usually related not only to mechanical parts but also to servomotors and the necessary electronics to efficiently control such a robotic system. Therefore, large, middle, but even small walking robots capable of traversing rough terrains can be very costly because of all the required equipment. On the other hand, using intelligent servomotors with the position control and feedback, affordable hexapod walking robots are becoming increasingly available. However, additional sensors may still be needed to stabilize the robot motion on rough terrains, e.g., inclinometers or inertial measurement units, force or tactile sensors to detect the ground contact point of the leg foot-tip. In this work, we present a minimalistic approach for adaptive locomotion control using only the servomotors position feedback. Adaptive fine-tuning of the proposed controller is supported by a dynamic model of the robot leg accompanied by the model of the internal servomotor controller. The models enable timely detection of the leg contact point with the ground and reduce developed stress and torques applied to the robot construction and servomotors without any additional sensor feedback. The presented results support that the proposed approach reliably detects the ground contact point, and thus enable traversing rough terrains with small, affordable hexapod walking robot.