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IEEE Access
Article . 2025 . Peer-reviewed
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IEEE Access
Article . 2025
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Nonlinear Programming-Based Robot Motion Planning for Automatic Gait Measurement of a Passing Pedestrian in Corridors

Authors: Kazuyuki Hayashide; Mitsuhiro Takahashi; Masaki Takahashi;

Nonlinear Programming-Based Robot Motion Planning for Automatic Gait Measurement of a Passing Pedestrian in Corridors

Abstract

Patrol robots in hospital wards are expected not only to ensure the safety of their movements, but also to perform gait measurement as part of their monitoring functions. In this study, we present a system that enables a patrol robot to perform a 5-meter walk test (5mWT) on passing pedestrians in a corridor. The pedestrian’s position and velocity are measured sequentially, and the robot’s trajectory is generated based on the results using a nonlinear programming method, followed by Model Predictive Control tracking. This allows for adaptive gait measurement during passing interactions, taking into account arbitrary pedestrian trajectories. Furthermore, a parameter estimation method tailored to the characteristics of the acquired data, namely whole-body, continuous and multi-view measurements, is proposed. Through simulation and experiments, we confirmed the feasibility of the measurement operation and accuracy of the derived gait parameters. The proposed method can not only be used anywhere, but also measure gait over a long distance with high accuracy using a single sensor. Moreover, it could contribute to the realization of gait measurement without pedestrian’s tension.

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Keywords

5-meter Walk Test (5mWT), nonlinear programming, robot motion planning, Electrical engineering. Electronics. Nuclear engineering, gait measurement, TK1-9971

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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