A two-stage optimal motion planner for autonomous agricultural vehicles

A two-stage optimal motion planner for autonomous agricultural vehicles This paper presents a two-stage motion planning algorithm which can compute low-cost motions for autonomous agricultural vehicles, for a given cost function defined over the entire path (e.g., shortest path, maximum clearance, etc.). In the first stage, the algorithm utilizes randomized motion planning to explore the space of possible motions and computes a feasible sub-optimal trajectory. In the second stage, the optimization of the stage-1 motion is formulated within the optimal control framework and function-space gradient descent is used to minimize the cost of the entire motion. The numerical results suggest that the two-stage motion planner can compute optimal or quasi-optimal motions in free space very quickly. In the presence of obstacles however, the execution time increases significantly. Furthermore, kino-dynamic, or dynamic motion models seem to be necessary in order to produce smooth motion trajectories. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

A two-stage optimal motion planner for autonomous agricultural vehicles

Loading next page...
 
/lp/springer_journal/a-two-stage-optimal-motion-planner-for-autonomous-agricultural-0fdCXEyoCc
Publisher
Kluwer Academic Publishers-Plenum Publishers
Copyright
Copyright © 2006 by Springer Science+Business Media, LLC
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-006-9022-9
Publisher site
See Article on Publisher Site

Abstract

This paper presents a two-stage motion planning algorithm which can compute low-cost motions for autonomous agricultural vehicles, for a given cost function defined over the entire path (e.g., shortest path, maximum clearance, etc.). In the first stage, the algorithm utilizes randomized motion planning to explore the space of possible motions and computes a feasible sub-optimal trajectory. In the second stage, the optimization of the stage-1 motion is formulated within the optimal control framework and function-space gradient descent is used to minimize the cost of the entire motion. The numerical results suggest that the two-stage motion planner can compute optimal or quasi-optimal motions in free space very quickly. In the presence of obstacles however, the execution time increases significantly. Furthermore, kino-dynamic, or dynamic motion models seem to be necessary in order to produce smooth motion trajectories.

Journal

Precision AgricultureSpringer Journals

Published: Sep 14, 2006

References

  • Automatic guidance for agricultural vehicles in Europe
    Keicher, R; Seufert, H

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from Google Scholar, PubMed
Create lists to organize your research
Export lists, citations
Access to DeepDyve database
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off