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Chapter Plan: Locomotion and Control

This document outlines the plan for the chapter "Locomotion and Control".

Summary​

This chapter explores the fascinating and complex problem of how to make a humanoid robot walk, run, and interact with its environment. We will delve into the fundamental principles of bipedal locomotion, including the concepts of the Zero Moment Point (ZMP) and the Linear Inverted Pendulum Model (LIPM). We will then move on to more advanced control strategies, such as Model Predictive Control (MPC), which allow for more dynamic and adaptive behaviors. Finally, we will examine the challenges of grasping and manipulation.

Learning Objectives​

  • Understand the concept of the Zero Moment Point (ZMP) and its importance in bipedal locomotion.
  • Explain the Linear Inverted Pendulum Model (LIPM) and how it is used to generate walking patterns.
  • Describe the principles of Model Predictive Control (MPC) and its application in robotics.
  • Identify the key challenges in robotic grasping and manipulation.

Key Topics​

  1. Principles of Bipedal Locomotion
    • The Zero Moment Point (ZMP)
    • The Linear Inverted Pendulum Model (LIPM)
    • Generating walking patterns
  2. Advanced Control Strategies
    • Model Predictive Control (MPC)
    • Whole-body control
    • Compliance and force control
  3. Grasping and Manipulation
    • Grasp planning
    • In-hand manipulation
    • The role of tactile sensing

Required Citations​

  • Vukobratović, M., & Borovac, B. (2004). Zero-moment point—thirty five years of its life. International Journal of Humanoid Robotics, 1(01), 157-173.
  • Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K., & Hirukawa, H. (2003). Biped walking pattern generation by using preview control of zero-moment point. In 2003 IEEE International Conference on Robotics and Automation (Cat. No. 03CH37422) (Vol. 2, pp. 1620-1626). IEEE.
  • Wieber, P. B. (2006). Trajectory free optimal control for stable walking of biped robots. In 2006 6th IEEE-RAS International Conference on Humanoid Robots (pp. 1-6). IEEE.