Rate of change of angular momentum and balance maintenance of biped robots

Abstract — In order to engage in useful activities upright legged creatures must be able to maintain balance. Despite recent advances, the understanding, prediction and control of biped balance in realistic dynamical situations remain an unsolved problem and the subject of much research in robotics and biomechanics. Here we study the fundamental mechanics of rotational sta-bility of multi-body systems with the goal to identify a general stability criterion. Our research focuses on ḢG, the rate of change of centroidal angular momentum of a robot, as the physical quantity containing its stability information. We propose three control strategies using ḢG that can be used for stability recapture of biped robots. For free walk on horizontal ground, a derived criterion refers to a point on the foot/ground surface of a robot where the total ground reaction force would have to act such that ḢG = 0. This new criterion generalizes earlier concepts such as GCoM, CoP, ZMP, and FRI point, and extends their applicability. I

Push Recovery of a Position-Controlled Humanoid Robot Based on Capture Point Feedback Control

In this paper, a combination of ankle and hip strategy is used for push recovery of a position-controlled humanoid robot. Ankle strategy and hip strategy are equivalent to Center of Pressure (CoP) and Centroidal Moment Pivot (CMP) regulation respectively. For controlling the CMP and CoP we need a torque-controlled robot, however most of the conventional humanoid robots are position controlled. In this regard, we present an efficient way for implementation of the hip and ankle strategies on a position controlled humanoid robot. We employ a feedback controller to compensate the capture point error. Using our scheme, a simple and practical push recovery controller is designed which can be implemented on the most of the conventional humanoid robots without the need for torque sensors. The effectiveness of the proposed approach is verified through push recovery experiments on SURENA-Mini humanoid robot under severe pushes

Ground reaction force sensor fault detection and recovery method based on virtual force sensor for walking biped robots

This paper presents a novel method for ground force sensor faults detection and faulty signal reconstruction using Virtual force Sensor (VFS) for slow walking bipeds. The design structure of the VFS consists of two steps, the total ground reaction force (GRF) and its location estimation for each leg based on the center of mass (CoM) position, the leg kinematics, and the IMU readings is carried on in the first step. In the second step, the optimal estimation of the distributed reaction forces at the contact points in the feet sole of walking biped is carried on. For the optimal estimation, a constraint model is obtained for the distributed reaction forces at the contact points and the quadratic programming optimization method is used to solve for the GRF. The output of the VFS is used for fault detection and recovery. A faulty signal model is formed to detect the faults based on a threshold, and recover the signal using the VFS outputs. The sensor offset, drift, and frozen output faults are studied and tested. The proposed method detects and estimates the faults and recovers the faulty signal smoothly. The validity of the proposed estimation method was confirmed by simulations on 3D dynamics model of the humanoid robot SURALP while walking. The results are promising and prove themselves well in all of the studied fault cases

Ground Reference Points in Legged Locomotion: Definitions, Biological Trajectories and Control Implications

The Zero Moment Point (ZMP) and Centroidal Moment Pivot (CMP) are important ground reference points used for motion identification and control in biomechanics and legged robotics. Using a consistent mathematical notation, we define and compare the ground reference points. We outline the various methodologies that can be employed in their estimation. Subsequently, we analyze the ZMP and CMP trajectories for level-ground, steady-state human walking. We conclude the chapter with a discussion of the significance of the ground reference points to legged robotic control systems. In the Appendix, we prove the equivalence of the ZMP and the center of pressure for horizontal ground surfaces, and their uniqueness for more complex contact topologies. Since spin angular momentum has been shown to remain small throughout the walking cycle, we hypothesize that the CMP will never leave the ground support base throughout the entire gait cycle, closely tracking the ZMP. We test this hypothesis using a morphologically realistic human model and kinetic and kinematic gait data measured from ten human subjects walking at self-selected speeds. We find that the CMP never leaves the ground support base, and the mean separation distance between the CMP and ZMP is small (14 % of foot length), highlighting how closely the human body regulates spin angular momentum in level ground walking

Combined Controllers that Follow Imperfect Input Motions for Humanoid Robots

Humanoid robots have the potential to become a part of everyday life as their hardware and software challenges are being solved. In this paper we present a system that gets as input a motion trajectory in the form of motion capture data, and produces a controller that controls a humanoid robot in real-time to achieve a motion trajectory that is similar to the input motion data. The controller expects the input motion data not to be dynamically feasible for the robot and employs a combined controller with corrective components to keep the robot balanced while following the motion. Since the system can run in real-time, it can be thought of a candidate for teleoperation of humanoid robots using motion capture hardware

Cooperative Control Design for Robot-Assisted Balance During Gait

Avoiding falls is a challenge for many persons in aging societies, and balance dysfunction is a major risk factor. Robotic solutions to assist human gait, however, focus on average kinematics, and less on instantaneous balance reactions. We propose a controller that only intervenes when needed, and that avoids stability issues when interacting with humans: Assistance is triggered only when balance is lost, and this action is purely feed-forward. Experiments show that subjects who start falling during gait can be uprighted by such feed-forward assistive force