Dynamic optimization of two methods of the long jump

Abstract

In this thesis, I analyzed, modelled, and optimized two different techniques of the long jump: the hitchkick and hang. Using video data, I made a dynamic model of both techniques, then created a cost function that took torques and angles into consideration to simulate physical limitations. Using a function minimizing optimizer, trajectories were simulated over a range of torque limits and angle penalties. Over the course of 292 simulations, we found that the hitchkick technique improved jump distances more than the hang technique, improving by up to 34.65% with an average of 7.7% while the hang technique increased jump distance by a maximum of 30.21%, with an average of -15.89%.