抄録
The objective of long jumping is try and jumping as far as possible by stepping on a take off board and landing in the sand pit. In the long jump landing, athletes are affected by the dynamics of the reaction force of the sand pit that is different from the hard surface reaction force. Therefore, in order to obtain a good landing motion, it is necessary to simultaneously analyze the dynamics of sand and athletes. The aim of this study is to obtain an optimal landing motion in the long jump by Multi-Objective Genetic Algorithm using a long jump model. This model is composed of two elements, which are a musculoskeletal model and landing pit model. The human body model is based on a multi body model containing eight rigid links and nineteen Hill-type muscles. The sand pit is modeled as particles assembly. The particles collision model consists of several forces, including a spring force which forces the particle apart, and a dashpot force which causes damping. Generally, it is very time-consuming to calculate the optimal motion and particle calculation. Here, this paper proposes the floating sand pit model which is suited to optimization of landing motion. Optimization using the proposed model was conducted by coupled simulation of human and sand pit.
