The average speed of motion and optimal power consumption in biped robots

Abstract

One of the issues that have garnered little attention, but that is nevertheless important for developing practical robots, is optimal walking conditions like power consumption during walking. The main contribution of this research is to prepare a correct walking pattern for humans who have a problem with their walking and also study the effect of average motion speed on optimal power consumption. In this study, we firstly optimize the stability and minimize the power consumption of the robot during the single support phase using parameter optimization. Our approach is based on the well-known Zero Moment Point method to calculate the stability of the proposed biped robot. Secondly, we performed experiments on healthy male, age 29 years, to analyze human walking by placing 28 markers, attached to anatomical positions and two power plates for a distance of more than one gait cycle at an average speed of 1.23 ± 0.1 m s−1 validate our results for motion analysis of correct walking ability. Our model was continuously validated by comparing the results of our empirical evaluation against the prediction of our model. The errors between experimental test and our prediction were about 4%–11% for the joint trajectories and about 0.2%–0.5% for the ground reaction forces which is acceptable for our prediction. Due to the presented model and optimized issue and predicted path, the robot can move like a person in a way that has maximum stability along with the minimum power consumption. Finally, the robot was able to walk like a specific person that we considered. This study is a case study and also can be generalized to all samples and can perform these procedures to another person’s with different features.

Thermodynamics of animal locomotion

“…Our model may apply to the description of the locomotion of all living organisms using a reduced set of physiological parameters, easily extractable from the literature or from experiments, allowing systematic comparison across species. It constitutes also a bridge between studies of animal locomotion and robot locomotion in terms of COT and gait adaptation [37][38][39], as adaptability, acquired by an increase of the number of limbs, competes with the need to minimize energy consumption. Hence, an adopted solution cannot be simultaneously adapted and adaptable: the more efficient the solution, the narrower the optimal operating range, implying that optimization in the sense of adaptability to changing environments and, on the contrary, adaptability to a stable environment, results in differing evolutionary strategies [22].…”

A grid gradient approximation method of energy-efficient gait planning for biped robots

“…One is to utilize high-speed optical motion capture systems to obtain data on human motion according to external characteristics of human walking and apply these features to the generation of robot motion modes. 5,6 The other approach is to use a central pattern generator to simulate the neural network control of human walking to generate rhythmic signals, thereby solving the problem of robot gait generation. [7][8][9] The third approach is to simplify the biped robot into a linear inverted pendulum model consisting of a point mass and a massless telescopic leg [10][11][12][13] or a cart-table model consisting of a table without mass and a cart driving on the table with all the mass concentrated in it.…”