This two-part paper discusses the analysis and control of legged locomotion in terms of N-step capturability: the ability of a legged system to come to a stop without falling by taking N or fewer steps. We consider this ability to be crucial to legged locomotion and a useful, yet not overly restrictive criterion for stability. Part 1 introduced the N-step capturability framework and showed how to obtain capture regions and control sequences for simplified gait models. In Part 2, we describe an algorithm that uses these results as approximations to control a humanoid robot. The main contributions of this part are (1) step location adjustment using the 1-step capture region, (2) novel instantaneous capture point control strategies, and 3) an experimental evaluation of the 1-step capturability margin. The presented algorithm was tested using M2V2, a 3D force-controlled bipedal robot with 12 actuated degrees of freedom in the legs, both in simulation and in physical experiments. The physical robot was able to recover from forward and sideways pushes of up to 21 Ns while balancing on one leg and stepping to regain balance. The simulated robot was able to recover from sideways pushes of up to 15 Ns while walking, and walked across randomly placed stepping stones.

No abstract

The estimation of the centre of mass position in humans is usually based on biomechanical models developed from anthropometric tables. This method can potentially introduce errors in studies involving elderly people, since the ageing process is typically associated with a modification of the distribution of the body mass. In this paper, an alternative technique is proposed, and evaluated with an experimental study on 9 elderly volunteers. The technique is based on a virtual chain, identified from experimental data and locating the subject's centre of mass. Its configuration defines the location of the centre of mass, and is a function of the anatomical joint angles measured on the subject. This method is a valuable investigation tool in the field of geronto-technology, since it overcomes some of the problems encountered with other CoM estimation methods.

Bipedal robots are currently either slow, energetically inefficient and/or require a lot of control to maintain their stability. This paper introduces the FastRunner, a bipedal robot based on a new leg architecture. Simulation results of a Planar FastRunner demonstrate that legged robots can run fast, be energy efficient and inherently stable. The simulated FastRunner has a cost of transport of 1.4 and requires only a local feedback of the hip position to reach 35.4 kph from stop in simulation.

This paper proposes a new technique to estimate the center of mass (CoM) of mechanical systems defined by an articulated set of rigid bodies. This technique is based on the use of the statically equivalent serial chain, a serial chain representation on any multi-link branched chain. Through the use of this model, and without any knowledge of each individual body’s CoM or CoM location, a simple method to estimate the mechanical system’s CoM is developed. This method is validated with the CoM estimation of the Hoap-3 humanoid robot. A sensitivity calculation for estimating the CoM in this way is also presented.

This paper proposes a method for modeling the Center of Mass (CoM) of humanoid robots. The method is based on the Statically Equivalent Serial Chain (SESC) model, a serial chain representation of any multi-link branched chain. An algorithm is presented to automatically construct the SESC of a symmetric anthropomorphic architecture. We also show the use of SESC modeling in the projection of the CoM when the kinematic chain is not positioned on a horizontal plane. Finally, after validating these developments on the HOAP-3 experimental humanoid robot platform, we discuss the interest of this modeling in other areas of research.

This paper proposes an analysis of the manipulability of the Center of Mass (CoM) of humanoid robots. Starting from the dynamic equations of humanoid robots, the operational space formulation is used to express the dynamics of humanoid robots at their CoM and under their specific characteristics: a free-floating base, forces at contact points, and dynamic balance constraints. After a review of the kinematic manipulability of the CoM, the concept of dynamic manipulability of the CoM is introduced. The latter represents the ability of a humanoid robot to generate a spatial motion under a stability criterion. The size and shape of the dynamic manipulability of the CoM are a function of the joint torque limitations, the contact forces and the zero moment point used as a stability criteria. Two calculations of the CoM dynamic manipulability are proposed, a fast ellipsoid approximation, and the exact polyhedron computation. A case study illustrates the proposed approach on the HOAP3 humanoid robot and its use for mechanical design optimization.

No abstract