Descriptive parameter optimization method for energy-saving gait planning of biped robots

Low energy efficiency is an important factor restricting the application and development of biped robots. In this article, an energy-saving walking control method using descriptive parameter optimization to obtain the gait type with minimum energy consumption is proposed. The algorithm evaluates the energy consumed during walking considering the load torque and angular velocity of all joint actuators of the five-mass simplified model of the robot. A gait database with the step length, gait type and stability margin as the input and gait parameters and energy consumption as the output is constructed, and the gait adapted to the zero-moment point region is dynamically adjusted during walking to realize a compromise between the robot walking stability and energy consumption. In the gait parameter optimization part of the algorithm, a mapping relationship between the descriptive parameters and body trajectory is established. Through parameter sampling and inverse kinematics calculations, seeds are selected from the sample set according to the stability margin, and the gradient descent method of directional acceleration is used to approximate the minimum energy consumption under the descriptive parameters in the neighborhood of the seeds. In the gait synthesis part of the algorithm, according to the given walking task and the energy consumption-related items in the gait database, the walking trajectory with minimum energy consumption is planned. In real-time walking, the database is queried according to the planned step sequence, the gait parameters are obtained, the robot joint movement is controlled, the feedback zero-moment point is calculated from the robot foot pressure, and the database input query is adjusted according to the trajectory deviation to simultaneously achieve walking stability and reduce energy consumption. To determine the effectiveness of the algorithm, dynamic simulation experiments and real robot walking experiments are carried out. The experimental results show that our algorithm has a significant energy-saving effect. The experimental videos are available at https://github.com/xkluzq/biped-robot.