Sep 03, 2015

Webinar: Simulation-Based Design of Devices to Enhance a Standing Long Jump

Learn about an optimization framework for synthesizing human standing long jumps and designing devices to improve performance

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A recording of the event is available for viewing. The model and code for dynamic optimization are available at: https://simtk.org/home/predictive_slj.

Details

Title:Simulation-Based Design of Devices to Enhance a Standing Long Jump
Speaker: Carmichael Ong, Stanford University
Time: Thursday, September 3, 2015 at 10:00 a.m. Pacific Daylight Time

Abstract

Advances in robotic technology have recently enabled the development of wearable devices aimed at assisting human movement. A major challenge in their development is characterizing the human-robot interaction. This webinar covers our work in understanding these interactions in a standing long jump.

This presentation follows our recent paper [1] in which we present an optimization framework to synthesize realistic human standing long jumps and investigate how simulated wearable robotic devices can improve jump performance. We will describe our planar model driven by physiological torque actuators to represent human musculoskeletal dynamics. We will present our formulation of the dynamic optimization problem to find the actuation pattern to maximize jump distance and will compare the solution with kinematic and kinetic features of human jumps from experiments. We will then show how we modelled active and passive devices based on existing devices and added these devices to lower limb joints. Using the same optimization framework to find actuation patterns for physiological and device actuators simultaneously, we found the simulated jump distance could be increased by about 1 meter.

This framework was also shared with students in a class taught at Stanford University who were tasked to design a suit to maximize jump distance. We will present their findings that using both active and passive components together may increase jump distance to twice as long as the unassisted case. These results demonstrate that a dynamic optimization framework can be used to simulate a standing long jump and is flexible enough to investigate human-robot interaction.

[1] Ong CF, Hicks, JL, Delp SL, "Simulation-Based Design for Wearable Robotic Systems: An Optimization Framework for Enhancing a Standing Long Jump," IEEE Trans Biomed Eng, 2015.

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