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Erschienen in: Autonomous Robots 2/2017

02.03.2016

Dynamically feasible, energy efficient motion planning for skid-steered vehicles

verfasst von: Nikhil Gupta, Camilo Ordonez, Emmanuel G. Collins Jr.

Erschienen in: Autonomous Robots | Ausgabe 2/2017

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Abstract

Recent research has developed experimentally verified dynamic models for skid-steered wheeled vehicles and used these results to derive a power model for this important class of all-terrain vehicles. As presented in this paper, based on the torque limitations of the vehicle motors, the dynamic model can be used to develop payload and terrain-dependent minimum turn radius constraints and the power model can be used to predict the energy consumption of a given trajectory. This paper uses these results along with sampling based model predictive optimization to develop an effective methodology for generating dynamically feasible, energy efficient trajectories for skid-steered autonomous ground vehicles (AGVs) and compares the resultant trajectories with those based on the standard distance optimal trajectories. The simulated and experimental results consider an AGV moving at a constant forward velocity on both wood and asphalt surfaces under various payloads. The results show that a small increase in the distance of a trajectory over the distance optimal trajectory can result in a dramatic savings in the AGV’s energy consumption. They also show that distance optimal planning can often produce trajectories that violate the motor torque constraints for skid-steered AGVs, which can result in poor navigation performance.

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Fußnoten
1
A modular wooden surface was used because it can be attached to a variable slope in the authors’ lab for future experiments that focus on sloped surfaces.
 
2
This paper has supplementary downloadable material (Motion_planning.zip) showing the motion planning results for movement on both wood and asphalt surfaces as presented in this paper.
 
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Metadaten
Titel
Dynamically feasible, energy efficient motion planning for skid-steered vehicles
verfasst von
Nikhil Gupta
Camilo Ordonez
Emmanuel G. Collins Jr.
Publikationsdatum
02.03.2016
Verlag
Springer US
Erschienen in
Autonomous Robots / Ausgabe 2/2017
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-016-9550-8

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