Motor Control Insights on Walking Planner and its Stability
Carlo Tiseo, Kalyana C Veluvolu, Wei Tech Ang

TL;DR
This paper introduces a potential energy-based model for human-like walking planning in bipedal robots, improving trajectory accuracy and stability assessment, with applications in rehabilitation robotics and neuroscience.
Contribution
It presents a novel task-space planner that uses potential energy models and human locomotor strategies to generate realistic CoM and foot trajectories, enhancing stability analysis.
Findings
Generated CoM and foot swing trajectories align with human strategies.
Significantly reduced error in CoM vertical trajectory estimation.
Model enables stability assessment based on body kinematics.
Abstract
The application of biomechanic and motor control models in the control of bidedal robots (humanoids, and exoskeletons) has revealed limitations of our understanding of human locomotion. A recently proposed model uses the potential energy for bipedal structures to model the bipedal dynamics, and it allows to predict the system dynamics from its kinematics. This work proposes a task-space planner for human-like straight locomotion that target application of in rehabilitation robotics and computational neuroscience. The proposed architecture is based on the potential energy model and employs locomotor strategies from human data as a reference for human behaviour. The model generates Centre of Mass (CoM) trajectories, foot swing trajectories and the Base of Support (BoS) over time. The data show that the proposed architecture can generate behaviour in line with human walking strategies for…
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Taxonomy
TopicsRobotic Locomotion and Control
