Optimized Joint-Torques Trajectory Planning for Bipedal Walking Robots

2008 ◽  
Author(s):  
Dau Van-Huan ◽  
Chee-Meng Chew ◽  
Aun-Neow Poo
Keyword(s):  
Trajectory Planning ◽  
Bipedal Walking ◽  
Walking Robots ◽  
Joint Torques

scholarly journals Galloping Trajectory Generation of a Legged Transport Robot Based on Energy Consumption Optimization

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Yaguang Zhu ◽  
Tong Guo
Keyword(s):  
Energy Consumption ◽  
Trajectory Planning ◽  
Stance Phase ◽  
Gait Cycle ◽  
Complex Surface ◽  
Walking Robots ◽  
Joint Torques ◽  
Energy Consumption Optimization ◽  
System Energy ◽  
Lift Off

Legged walking robots have very strong operation ability in the complex surface and they are very suitable for transportation of tools, materials, and equipment in unstructured environment. Aiming at the problems of energy consumption of legged transport robot during the fast moving, a method of galloping trajectory planning based on energy consumption optimization is proposed. By establishing transition angle polynomials of flight phase, lift-off phase, and stance phase and constraint condition between each state phase, the locomotion equations of the ellipse trajectory are derived. The transition angle of each state phase is introduced into the system energy consumption equations, and the energy optimization index based on transition angles is established. Inverse kinematics solution and trajectory planning in one gait cycle are applied to genetic algorithm process to solve the nonlinear programming problem. The results show that the optimized distribution of transition angles of state phases is more reasonable, and joint torques and system energy consumption are reduced effectively. Thus, the method mentioned above has a great significance to realize fast operation outdoors of transport robot.

ZMP-Based Trajectory Generation for Bipedal Robots Using Quadratic Programming

2020 ◽  
pp. 266-285
Author(s):  
Sergei Savin
Keyword(s):  
Numerical Simulation ◽  
Quadratic Programming ◽  
Center Of Mass ◽  
Trajectory Generation ◽  
Bipedal Walking ◽  
Walking Robots ◽  
Bipedal Robots ◽  
Change Of Variables ◽  
Viable Solution ◽  
Modern Optimization

In this chapter, the problem of trajectory generation for bipedal walking robots is considered. A number of modern techniques are discussed, and their limitations are shown. The chapter focuses on zero-moment point methods for trajectory generation, where the desired trajectory of that point can be used to allow the robot to keep vertical stability if followed, and presents an instrument to calculate the desired trajectory for the center of mass for the robot. The chapter presents an algorithm based on quadratic programming, with an introduction of a slack variable to make the problem feasible and a change of variables to improve the numeric properties of the resulting optimization problem. Modern optimization tools allow one to solve such problems in real time, making it a viable solution for trajectory planning for the walking robots. The chapter shows a few results from the numerical simulation made for the algorithm, demonstrating its properties.

scholarly journals Constrained Quadratic Programming and Neurodynamics-Based Solver for Energy Optimization of Biped Walking Robots

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Liyang Wang ◽  
Ming Chen ◽  
Xiangkui Jiang ◽  
Wei Wang
Keyword(s):  
Energy Consumption ◽  
Quadratic Programming ◽  
Energy Optimization ◽  
Biped Robot ◽  
High Energy ◽  
Walking Robots ◽  
Biped Robots ◽  
Biped Walking ◽  
Joint Torques ◽  
Force Moment

The application of biped robots is always trapped by their high energy consumption. This paper makes a contribution by optimizing the joint torques to decrease the energy consumption without changing the biped gaits. In this work, a constrained quadratic programming (QP) problem for energy optimization is formulated. A neurodynamics-based solver is presented to solve the QP problem. Differing from the existing literatures, the proposed neurodynamics-based energy optimization (NEO) strategy minimizes the energy consumption and guarantees the following three important constraints simultaneously: (i) the force-moment equilibrium equation of biped robots, (ii) frictions applied by each leg on the ground to hold the biped robot without slippage and tipping over, and (iii) physical limits of the motors. Simulations demonstrate that the proposed strategy is effective for energy-efficient biped walking.

scholarly journals Humanoid Walking Robot: Modeling, Inverse Dynamics, and Gain Scheduling Control

2010 ◽  
Vol 2010 ◽  
pp. 1-19 ◽  
Author(s):  
Elvedin Kljuno ◽  
Robert L. Williams
Keyword(s):  
Inverse Dynamics ◽  
Reference Model ◽  
Tracking Error ◽  
Gain Scheduling ◽  
Bipedal Walking ◽  
Walking Robot ◽  
Concentrated Mass ◽  
Mass Model ◽  
Nonlinear Gain ◽  
Joint Torques

This article presents reference-model-based control design for a 10 degree-of-freedom bipedal walking robot, using nonlinear gain scheduling. The main goal is to show concentrated mass models can be used for prediction of the required joint torques for a bipedal walking robot. Relatively complicated architecture, high DOF, and balancing requirements make the control task of these robots difficult. Although linear control techniques can be used to control bipedal robots, nonlinear control is necessary for better performance. The emphasis of this work is to show that the reference model can be a bipedal walking model with concentrated mass at the center of gravity, which removes the problems related to design of a pseudo-inverse system. Another significance of this approach is the reduced calculation requirements due to the simplified procedure of nominal joint torques calculation. Kinematic and dynamic analysis is discussed including results for joint torques and ground force necessary to implement a prescribed walking motion. This analysis is accompanied by a comparison with experimental data. An inverse plant and a tracking error linearization-based controller design approach is described. We propose a novel combination of a nonlinear gain scheduling with a concentrated mass model for the MIMO bipedal robot system.

Sign in / Sign up

Export Citation Format

Share Document