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3D Underactuated Bipedal Walking via H-LIP based Gait Synthesis and Stepping Stabilization (2101.09588v3)

Published 23 Jan 2021 in cs.RO

Abstract: In this paper, we holistically present a Hybrid-Linear Inverted Pendulum (H-LIP) based approach for synthesizing and stabilizing 3D foot-underactuated bipedal walking, with an emphasis on thorough hardware realization. The H-LIP is proposed to capture the essential components of the underactuated and actuated part of the robotic walking. The robot walking gait is then directly synthesized based on the H-LIP. We comprehensively characterize the periodic orbits of the H-LIP and provably derive the stepping stabilization via its step-to-step (S2S) dynamics, which is then utilized to approximate the S2S dynamics of the horizontal state of the center of mass (COM) of the robotic walking. The approximation facilities a H-LIP based stepping controller to provide desired step sizes to stabilize the robotic walking. By realizing the desired step sizes, the robot achieves dynamic and stable walking. The approach is fully evaluated in both simulation and experiment on the 3D underactuated bipedal robot Cassie, which demonstrates dynamic walking behaviors with both high versatility and robustness.

Citations (62)

Summary

  • The paper introduces an H-LIP framework that maps state dynamics to precise step sizes, enabling systematic gait synthesis for stable bipedal locomotion.
  • It details a geometric characterization of periodic orbits, reducing the need for complex trajectory optimization by leveraging direct state-to-gait mappings.
  • Experimental validation on the robot Cassie confirms that the deadbeat stepping controller ensures robust balance and adaptability over uneven terrain.

Understanding 3D Underactuated Bipedal Walking through the H-LIP Framework

The paper "3D Underactuated Bipedal Walking via H-LIP based Gait Synthesis and Stepping Stabilization" by Xiaobin Xiong and Aaron Ames, presents a systematic approach to addressing the challenges inherent in foot-underactuated bipedal walking, utilizing the Hybrid Linear Inverted Pendulum (H-LIP) model. In the context of robotics, achieving stable and dynamic bipedal locomotion is a complex task, especially when the foot-ground interaction is underactuated, as seen in various robotic designs prioritizing agility and simplicity.

The essence of the authors' methodology lies in leveraging the H-LIP framework to approximate and stabilize the underactuated dynamics of a bipedal robotic system. The H-LIP model abstracts the system dynamics into a lower-dimensional space by assuming a constant center of mass height and capturing the discrete step-to-step (S2S) control of the horizontal states through a passive pendulum model. This allows for a more straightforward synthesis of walking gaits by developing systematic mappings from H-LIP states to robot dynamics, thereby aligning robot behaviors with desired periodic trajectories.

Key Contributions and Findings

  1. Geometric Characterization of Periodic Orbits:
    • The paper provides a detailed characterization of Period-1 (P1) and Period-2 (P2) orbits within the H-LIP state space. Using phase portraits, it establishes the relationship between pre-impact states and their corresponding step sizes necessary to achieve periodic walking.
    • For any given desired velocity, the paper derives the unique state representations and step sizes required to realize these walking gaits, facilitating an analytical synthesis process based on achievable orbits.
  2. Establishment of the H-LIP Approach for Gait Synthesis:
    • By implementing a straightforward mapping from the H-LIP's predicted behaviors to actual robotic walking, the authors eliminate the need for complex trajectory optimization, thus making the control framework computationally efficient. Key parameters such as step frequency, vertical COM height, and swing foot trajectories are synthesized directly, supporting robust gait personalization and adaptability.
  3. Novel Stepping Controller Design:
    • The authors implement a deadbeat control approach, stabilizing the gait by computing desired step sizes based on the S2S dynamics of the H-LIP, which are then applied to the robot. This method encompasses a feedforward component and feedback correction for the robotic step sizes determined via a linear control strategy, enabling practical stabilization against dynamic uncertainties.
  4. Application to the Robot Cassie:
    • Extensive simulation and experimental validation on the 3D underactuated robot Cassie demonstrates the robustness, versatility, and efficiency of the H-LIP framework. Behaviorally, the approach supports a wide range of lateral, forward, and complex directional walking, including execution over uneven terrain and dynamic disturbances.

Practical and Theoretical Implications

The proposed framework demonstrates significant potential for advancing the robustness and adaptability of bipedal locomotion in robotics. Practically, it simplifies gait design for various robot configurations without necessitating detailed dynamic modeling, thus accommodating a range of hardware, environments, and operational conditions. This approach enhances the versatility of adaptive robotics, particularly in scenarios requiring immediate gait adjustments or responsiveness to unpredictable environmental interaction.

The paper's theoretical contributions enable a more profound understanding of how underactuated bipedal robots can effectively exploit minimalistic control designs for stable locomotion, providing insights into the fundamental geometric and dynamic properties of gait orbits. The delineation of periodic orbits and the systematic formulation of stepping control based on H-LIP dynamics present foundational strategies that can be expanded to other domains, such as humanoid robotics and legged locomotion beyond flat terrain.

Future Developments

The ongoing evolution of this framework could lead to more sophisticated modeling constructs incorporating adaptive gait synthesis and augmented state feedback mechanisms for real-time adjustment to drastic environmental shifts. Moreover, the integration of advanced data-driven techniques or real-time optimization can further refine the approximation and stability controls, enhancing the robot's capability to navigate complex, dynamic scenarios present in diverse operational landscapes. Overall, this paper marks a substantial step toward achieving reliable, efficient, and adaptable bipedal robotic locomotion.

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