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Optimization-Based Navigation for the DARPA Grand Challenge |
Abstract |
This research addresses the path planning … This research addresses the path planning problem
with a nonlinear optimization method running in real
time. An optimization problem is continually solved to find a
time-optimal, dynamically feasible trajectory from the vehicleâs
position to some receding horizon ahead (20m-70m forward).
The locally optimal numerical solver optimizes both the spatial
and temporal components of the trajectory simultaneously, and
feeds its output to a trajectory-following controller. The method
has been implemented and tested on a modified Ford E350
van. Using one stereo pair and four LADAR units as terrain
sensors, the vehicle was able to consistently traverse a 2 mile
obstacle course at the DGC qualifying event. At the main
DGC event, the vehicle drove 8 autonomous miles through the
Nevada desert before experiencing non-planning issues. During
this time, the planning system generated a plan 4.28 times
per second on average. This execution speed, coupled with a
feedback-based trajectory-following controller was shown to be
adequate at providing smooth and reliable obstacle avoidance
even on complicated terrain. cle avoidance
even on complicated terrain. +
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Authors | Dmitriy Kogan and Richard M. Murray + |
Funding | Correct-by-Construction Synthesis of Control Protocols for Aerospace Systems + |
ID | 2006k + |
Source | Submitted, 2006 Conference on Decision and Control + |
Tag | km06-cdc + |
Title | Optimization-Based Navigation for the DARPA Grand Challenge + |
Type | Conference Paper + |
Categories | Papers |
Modification date This property is a special property in this wiki.
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15 May 2016 06:17:35 + |
URL This property is a special property in this wiki.
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http://www.cds.caltech.edu/~murray/preprints/km06-cdc.pdf + |
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Optimization-Based Navigation for the DARPA Grand Challenge + | Title |
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