Walking is an essential part of almost all activities of daily living. We use different gait patterns in different situations, e.g., moving around the house, performing various sports, or when compensating for an injury. However, how humans perform this gait tailoring remains a partially unknown process. To this end, the influence of various performance metrics on the optimality and diversity of gait patterns can provide us with more insight. To analyse gait in terms of pattern diversity and performance metrics related to physical aspects, such as joint torque, fatigue, and manipulability, we propose a multi-metric gait analysis framework that simultaneously accounts for these parameters. We used a recorded set of versatile gait patterns that are already dynamically stable and physiologically feasible. To that end, 45 gait variations-varying in stride length, step height, and walking speed-were recorded in a motion capture experiment. Results of analysis using the recorded dataset are presented for a baseline case (with all optimisation weights set to one), which serves as the first step for future research, in particular giving insights into specific aspects of the gait, e.g., joint loading, long-term performance, and capacity to sustain ground reaction forces.
|Title of host publication||Proceedings of the 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)|
|Publication status||Published - 2022|
|Event||Humanoids 2022 IEEE-RAS 21st International Conference on Humanoid Robots - Okinawa, Japan|
Duration: 28 Nov 2022 → 30 Nov 2022
|Conference||Humanoids 2022 IEEE-RAS 21st International Conference on Humanoid Robots|
|Period||28/11/22 → 30/11/22|
Bibliographical noteGreen Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
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