Towards thruster-assisted bipedal locomotion for enhanced efficiency and robustness
This work addresses efficiency and robustness in bipedal locomotion for robotics applications, presenting an incremental improvement by leveraging thrusters for enhanced control during specific gait phases.
The paper tackles the problem of designing closed-loop feedback for thruster-assisted bipedal robot walking by fine-tuning joint trajectories to satisfy performance constraints, using a reference governor filter and predictive schemes to ensure hybrid invariance without relying on expensive numeric approaches.
In this paper, we will report our efforts in designing closed-loop feedback for the thruster-assisted walking of bipedal robots. We will assume for well-tuned supervisory controllers and will focus on fine-tuning the joints desired trajectories to satisfy the performance being sought. In doing this, we will devise an intermediary filter based on reference governors that guarantees the satisfaction of performance-related constraints. Since these modifications and impact events lead to deviations from the desired periodic orbits, we will guarantee hybrid invariance in a robust way by applying predictive schemes withing a very short time envelope during the gait cycle. To achieve the hybrid invariance, we will leverage the unique features in our model, that is, the thrusters. The merit of our approach is that unlike existing optimization-based nonlinear control methods, satisfying performance-related constraints during the single support phase does not rely on expensive numeric approaches. In addition, the overall structure of the proposed thruster-assisted gait control allows for exploiting performance and robustness enhancing capabilities during specific parts of the gait cycle, which is unusual and not reported before.