International Journal of Humanoid Robotics

This article presents a theoretical approach for modeling and controlling the stability of legged robots. The new proposed concept is two-fold: (a) the definition of the (m-d)-stability and (b) the definition of the Virtual Generalized Stabilizer. These concepts are developed throughout a theoretical and general approach to the dynamics of legged robots. Numerical results are analyzed through the simulated behavior of a biped robot recovering a statically stable state under two conditions: an unstable initial posture and an impulsive external force.

This paper suggests a generalized approach to the modeling of human and humanoid motion. Instead of the usual inductive approach that starts from the analysis of different situations of real motion (like bipedal gait and running; playing tennis, soccer, or volleyball; gymnastics on the floor or by using some gymnastic apparatus; etc.) and tries to make a generalization, we suggest a deductive approach: one starts by considering a completely general problem. Once the general model is formulated, one may derive different real situations as being special cases. Such an approach require a serious effort in formulating the general model. This paper is an attempt in this direction. The general methodology is explained and the feasibility is supported by applying the general model to two illustrative examples: first, a well-known situation — the single-support phase of a biped motion — and second, a completely different problem — gymnastic exercise on a horizontal bar.

Optimal gait cycles are generated for a seven-link biped using a parametric optimization method. A sagittal walking pattern, including a double-support phase divided into two sub-phases, is considered. Generalized joint coordinates are approximated by three-time differentiable spline-functions. These are the concatenation of 4-order polynomials linked together up to their third derivatives at connecting points — or knots — distributed along the motion time of each phase. Optimization parameters are the values of joint coordinates at the knots, plus the joint velocities, and possibly the joint accelerations, at transitions between successive phases. An integral amount of driving torques is minimized throughout the walking cycle. During the double support, constraint forces in the kinematically closed locomotion system are dealt with as additional actuating forces. For this reason, these are also minimized. Using the above optimization parameters, this basic optimal control problem is transformed into an optimization problem of mathematical programming. The latter is efficiently solved using a Sequential Quadratic Programming algorithm. The only kinematic data required for generating a gait cycle is the walking speed. Postural configurations between successive phases, step length, and relative length of single and double supports are optimized with respect to a given walking speed.

Research on humanoid robotics has up to now been focused on the control of manipulators and walking machines. The contributions of body torso torwards daily activities have been neglected. To address this deficient area of humanoid robotics research, we developed a unique flexible spine biped humanoid robot. Inspired by the rhythmic and wave-like motions commonly seen in swimming lamprey and in belly dancing, we investigated the possibility of controlling the spine of our robot using the lamprey central pattern generator (CPG). Experimental results show that our robot is capable of mimicing both basic and complex spine motions with fewer actuators than the human spine and using only three input parameters (global and extra excitations from the brainstem, plane of actions). Our work suggests that the CPG is a suitable controller for humanoid spine motions because it can control a high degree of freedom mechanical spine with minimized control parameters. No complex computations of spine trajectories are involved. Furthermore, since our robot can move its upper body dynamically while standing and without external supports, it may be used as a prototype for the next generation of humanoid robots.

Handwriting has always been considered an important human task, and accordingly it has attracted the attention of researchers working in biomechanics, physiology, and related fields. There exist a number of studies on this area. This paper considers the human–machine analogy and relates robots with handwriting. The work is two-fold: it improves the knowledge in biomechanics of handwriting, and introduces some new concepts in robot control. The idea is to find the biomechanical principles humans apply when resolving kinematic redundancy, express the principles by means of appropriate mathematical models, and then implement them in robots. This is a step forward in the generation of human-like motion of robots. Two approaches to redundancy resolution are described: (i) "Distributed Positioning" (DP) which is based on a model to represent arm motion in the absence of fatigue, and (ii) the "Robot Fatigue" approach, where robot movements similar to the movements of a human arm under muscle fatigue are generated. Both approaches are applied to a redundant anthropomorphic robot arm performing handwriting. The simulation study includes the issues of legibility and inclination of handwriting. The results demonstrate the suitability and effectiveness of both approaches.