Humanoid robot

Summary

A humanoid robot is a robot resembling the human body in shape. The design may be for functional purposes, such as interacting with human tools and environments, for experimental purposes, such as the study of bipedal locomotion, or for other purposes. In general, humanoid robots have a torso, a head, two arms, and two legs, though some humanoid robots may replicate only part of the body, for example, from the waist up. Some humanoid robots also have heads designed to replicate human facial features such as eyes and mouths. Androids are humanoid robots built to aesthetically resemble humans. History The concept of a humanoid robot originated in many different cultures around the world. Some of the earliest accounts of the idea of humanoid automata date to the 4th century BCE in Greek mythologies and various religious and philosophical texts from China. Physical prototypes of humanoid automata were later created in the Middle East, Italy, Japan, and France. Greece

Official source

https://en.wikipedia.org/wiki/Humanoid_robot

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Adaptive Task-Space Force Control for Humanoid-to-Human Assistance

Anastasia Bolotnikova

We envision a humanoid robot to serve as a source of additional motion-support forces in assistance for frail persons. In this context, we present a control strategy for a humanoid to adaptively regulate its assistive force contribution. First, we identify a human model torque control for optimal execution of a priori known motion task from sample recordings of this task performed by a healthy individual. We utilize the identified model in the proposed position discrepancy based observer of the human torque contribution, the unknown and unmeasurable variable. We propose an experience-based human contribution model learning strategy that allows to improve the human contribution estimate from trial-to-trial. The target assistive torque contribution is then calculated as the difference between the optimal torque required for the motion task and the estimated human contribution. The target assistive torque is integrated into a multi-robot quadratic programming task-space controller to compute the desired interaction force required for the robot to supply the necessary assistive torque for the human model. We use the non-optimal recordings of the human motion task to emulate human frailty and apply our adaptive force control strategy to demonstrate the results of a humanoid successfully assisting the simulated human model to restore the optimal motion task performance.

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Motion autonomy for humanoids: experiments on HRP-2 No. 14

This paper deals with whole-body motion planning and dynamic control for humanoid from two aspects: locomotion including manipulation and reaching. In the first part, we address a problem of simultaneous locomotion and manipulation planning that combines a geometric and kinematic motion planner with a dynamic humanoid motion generator. The second part deals with whole-body reaching tasks by using a generalized inverse kinematics (IK) method to fully exploit the high redundancy of the humanoid robot. Through experiments using humanoid platform HRP-2 No. 14 installed at LAAS-CNRS, we first verify the validity of each method. An integrated experiment is then presented that unifies the both results via visual perception to execute an object-fetching task. Copyright (C) 2009 John Wiley & Sons, Ltd.

2009

Humanoid robots are currently still far from reaching the impressive human walking capabilities. Among the different methods used to design walking controllers, those based on the Zero-Moment Point (ZMP) criterion are among the most popular, even if they induce intrinsic limitations in terms of energy consumption and robustness. In parallel, bio-inspired controllers are emerging. They overcome the ZMP-based limitations, but still miss robust stabilization rules to be validated on real robots. This contribution studies how to efficiently compute the ZMP in realtime on a robot walking with bio-inspired control rules, in order to detect when the robot stability is compromised.

IEEE2014