We introduce a new method of a biped walking pattern generation by using a preview control of the zero-moment point (ZMP). First, the dynamics of a biped robot is modeled as a running cart on a table which gives a convenient representation to treat ZMP. After reviewing conventional methods of ZMP based pattern generation, we formalize the problem as the design of a ZMP tracking servo controller. It is shown that we can realize such controller by adopting the preview control theory that uses the future reference. It is also shown that a preview controller can be used to compensate the ZMP error caused by the difference between a simple model and the precise multibody model. The effectiveness of the proposed method is demonstrated by a simulation of walking on spiral stairs.

/pdf/biped-walking-pattern-generation-by-using-preview-control-of-84qdve2k8v.pdf

Biped walking pattern generation by using preview control of zero-moment point

This paper is devoted to the permanence of the concept of Zero-Moment Point, widelyknown by the acronym ZMP. Thirty-five years have elapsed since its implicit presentation (actually before being named ZMP) to the scientific community and thirty-three years since it was explicitly introduced and clearly elaborated, initially in the leading journals published in English. Its first practical demonstration took place in Japan in 1984, at Waseda University, Laboratory of Ichiro Kato, in the first dynamically balanced robot WL-10RD of the robotic family WABOT. The paper gives an in-depth discussion of source results concerning ZMP, paying particular attention to some delicate issues that may lead to confusion if this method is applied in a mechanistic manner onto irregular cases of artificial gait, i.e. in the case of loss of dynamic balance of a humanoid robot. After a short survey of the history of the origin of ZMP a very detailed elaboration of ZMP notion is given, with a special review concerning “boundary cases” when the ZMP is close to the edge of the support polygon and “fictious cases” when the ZMP should be outside the support polygon. In addition, the difference between ZMP and the center of pressure is pointed out. Finally, some unresolved or insufficiently treated phenomena that may yield a significant improvement in robot performance are considered.

https://www.techfak.uni-bielefeld.de/~rhaschke/lehre/WS04/humanoids/papers/zmp-review.pdf

Zero-moment point — thirty five years of its life

We present the system overview and integration of the ASIMO autonomous robot that can function successfully in indoor environments. The first model of ASIMO is already being leased to companies for receptionist work. In this paper, we describe the new capabilities that we have added to ASIMO. We explain the structure of the robot system for intelligence, integrated subsystems on its body, and their new functions. We describe the behavior-based planning architecture on ASIMO and its vision and auditory system. We describe its gesture recognition system, human interaction and task performance. We also discuss the external online database system that can be accessed using internet to retrieve desired information, the management system for receptionist work, and various function demonstrations.

The intelligent ASIMO: system overview and integration

http://www.bcp.psych.ualberta.ca/~mike/Pearl_Street/PSYCO354/pdfstuff/Readings/Schaal1.pdf

Is imitation learning the route to humanoid robots

For 3D walking control of a biped robot we analyze the dynamics of a 3D inverted pendulum in which motion is constrained to move along an arbitrarily defined plane. This analysis yields a simple linear dynamics, the 3D linear inverted pendulum mode (3D-LIPM). Geometric nature of trajectories under the 3D-LIPM and a method for walking pattern generation are discussed. A simulation result of a walking control using a 12-DOF biped robot model is also shown.

The 3D linear inverted pendulum mode: a simple modeling for a biped walking pattern generation

In this paper, we present the mechanism, system configuration, basic control algorithm and integrated functions of the Honda humanoid robot. Like its human counterpart, this robot has the ability to move forward and backward, sideways to the right or the left, as well as diagonally. In addition, the robot can turn in any direction, walk up and down stairs continuously. Furthermore, due to its unique posture stability control, the robot is able to maintain its balance despite unexpected complications such as uneven ground surfaces. As a part of its integrated functions, this robot is able to move on a planned path autonomously and to perform simple operations via wireless teleoperation.

K. Hirai

Papers

The development of Honda humanoid robot