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Versatile Locomotion Planning and Control for Humanoid Robots.

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Summary

This study introduces a new framework for bipedal robot locomotion, combining trajectory optimization for walking robots plus (TOWR+) and an implicit hierarchical whole-body controller (IHWBC). The system enables versatile and stable walking behaviors in robots like DRACO.

Keywords:
humanoid robotslocomotionopen source softwaretrajectory optimizationwhole body control

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Area of Science:

  • Robotics
  • Control Systems
  • Machine Learning

Background:

  • Bipedal robot locomotion requires sophisticated motion planning and control to handle complex dynamics and constraints.
  • Existing methods often struggle with versatility, real-time computation, and seamless integration of planning and control modules.

Purpose of the Study:

  • To develop a novel locomotion framework for bipedal robots.
  • To introduce advanced motion planning (TOWR+) and whole-body control (IHWBC) methods.
  • To create a versatile, open-source software architecture (PnC) for integrating these components.

Main Methods:

  • Developed Trajectory Optimization for Walking Robots plus (TOWR+) for optimizing robot motion, contact timing, and locations.
  • Implemented Implicit Hierarchical Whole-Body Controller (IHWBC) to enforce contact constraints and task hierarchies.
  • Utilized a composite rigid body (CRB) model with a pre-trained centroidal inertia network for accurate dynamics modeling.
  • Introduced the Planning and Control (PnC) software architecture for modular integration and testing.

Main Results:

  • TOWR+ demonstrated effective optimization of base and end-effector motions, and contact parameters without complex solvers.
  • IHWBC successfully enforced unilateral contact constraints and task priorities, enabling flexible control.
  • The integrated TOWR+ and IHWBC framework was successfully demonstrated on the DRACO robot, achieving step-and-stop behaviors.
  • Experimental analysis validated the performance of TOWR+ across various bipedal robots and IHWBC for balancing on hardware.

Conclusions:

  • The proposed locomotion framework, integrating TOWR+ and IHWBC within the PnC architecture, offers a versatile and effective solution for bipedal robot locomotion.
  • The methods provide enhanced flexibility, smooth transitions, and robust performance in dynamic walking tasks.
  • The open-source PnC software facilitates modularity and scalability for future advancements in robot control.