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Optimization Based Motion Planning With Obstacles And Priorities

Greiff, Marcus LU and Robertsson, Anders LU (2017) 20th IFAC World Congress, 2017 In IFAC-PapersOnLine 50(1). p.11670-11676
Abstract
The goal of this work is to explore ways of generating state trajectories for dynamical systems subject to computational constraints, obstacles and priority assignment. The algorithms are developed for a miniature unmanned aerial vehicle (UAV) in a modular fashion and include (1) a genetic algorithm (GA) for solving the traveling salesman problem (TSP) with respect to priorities and obstacle avoidance, (2) a projective algorithm (PA) for finding the shortest paths around obstacles, (3) a quadratic program (QP) for minimum-snap polynomial trajectory generation subject to equality constraints to guarantee avoidance of static obstacles. Combined, the algorithms enable simple and computationally efficient motion planning with support in both... (More)
The goal of this work is to explore ways of generating state trajectories for dynamical systems subject to computational constraints, obstacles and priority assignment. The algorithms are developed for a miniature unmanned aerial vehicle (UAV) in a modular fashion and include (1) a genetic algorithm (GA) for solving the traveling salesman problem (TSP) with respect to priorities and obstacle avoidance, (2) a projective algorithm (PA) for finding the shortest paths around obstacles, (3) a quadratic program (QP) for minimum-snap polynomial trajectory generation subject to equality constraints to guarantee avoidance of static obstacles. Combined, the algorithms enable simple and computationally efficient motion planning with support in both R2 and R3 exemplified in a real-time implementation. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
UAV, motion planning , projective path, heuristic TSP , optimisation
in
IFAC-PapersOnLine
volume
50
issue
1
pages
7 pages
publisher
IFAC Secretariat
conference name
20th IFAC World Congress, 2017
external identifiers
  • scopus:85044864885
ISSN
2405-8963
DOI
10.1016/j.ifacol.2017.08.1677
language
English
LU publication?
yes
id
b12d27fd-e3ca-4b72-bbbe-3dc93a3b6cdc
date added to LUP
2017-11-27 20:44:09
date last changed
2018-04-22 04:34:02
@article{b12d27fd-e3ca-4b72-bbbe-3dc93a3b6cdc,
  abstract     = {The goal of this work is to explore ways of generating state trajectories for dynamical systems subject to computational constraints, obstacles and priority assignment. The algorithms are developed for a miniature unmanned aerial vehicle (UAV) in a modular fashion and include (1) a genetic algorithm (GA) for solving the traveling salesman problem (TSP) with respect to priorities and obstacle avoidance, (2) a projective algorithm (PA) for finding the shortest paths around obstacles, (3) a quadratic program (QP) for minimum-snap polynomial trajectory generation subject to equality constraints to guarantee avoidance of static obstacles. Combined, the algorithms enable simple and computationally efficient motion planning with support in both R2 and R3 exemplified in a real-time implementation.},
  author       = {Greiff, Marcus and Robertsson, Anders},
  issn         = {2405-8963},
  keyword      = {UAV,motion planning ,projective path,heuristic TSP ,optimisation },
  language     = {eng},
  month        = {10},
  number       = {1},
  pages        = {11670--11676},
  publisher    = {IFAC Secretariat},
  series       = {IFAC-PapersOnLine},
  title        = {Optimization Based Motion Planning With Obstacles And Priorities},
  url          = {http://dx.doi.org/10.1016/j.ifacol.2017.08.1677},
  volume       = {50},
  year         = {2017},
}