Towards Humanoids Operating Mobility Devices Designed for Humans

Abstract

Humanoid robotics is advancing rapidly, with significant potential to address challenges in disaster recovery, manufacturing, and healthcare. Despite progress, current humanoid capabilities remain limited, particularly in terms of efficient mobility over long distances. Integrating humanoid robots with personal transporters (PTs) like Segways, offers a promising solution, enabling them to operate more efficiently in human-centric environments such as factories, malls, and airports. This approach not only preserves the humanoid's ability to navigate complex, uneven terrain with its legs but also enhances versatility, allowing for faster, more energy-efficient movement on flat surfaces.

This thesis explores methods for enabling bipedal humanoids to operate PTs, focusing on the REEM-C humanoid riding a Segway x2 SE. The research begins by analyzing human interactions with Segways to reverse-engineer their internal controllers, leading to a high-fidelity simulation model. This model informs the development of control algorithms for the REEM-C, enabling successful simulation-based demonstrations of humanoid-driven Segway motions, including translational, rotational, and mixed maneuvers. Building on this, balance stabilization strategies are devised for actuated balance boards, addressing both frontal and sagittal plane control through an integration of admittance control strategies.

A comprehensive analysis of bimanual manipulation is also conducted, emphasizing manipulability and stability within a constrained workspace. Using a combined manipulability-stability metric, collision-free bimanual trajectories are generated, demonstrating improved stability during dynamic tasks such as manipulating objects of varying shapes and masses. This analysis underpins the implementation of bimanual manipulation strategies needed for operating the Segway’s LeanSteer handlebar.

The final contribution consolidates all findings, presenting a whole-body control strategy that enables the REEM-C to ride a Segway safely and effectively. A stack-of-tasks quadratic program is utilized to ensure stability, balance, and bimanual control in dynamic conditions. Experimental validation demonstrates the feasibility of this approach, showcasing the REEM-C’s ability to operate a Segway under real-world conditions. This research provides a step towards more versatile and adaptable humanoid mobility solutions for everyday human environments.