TY - GEN
T1 - Trajectory planning on grids
T2 - Considering speed limit constraints
AU - Chrpa, Lukáš
PY - 2011
Y1 - 2011
N2 - Trajectory (path) planning is a well known and thoroughly studied field of automated planning. It is usually used in computer games, robotics or autonomous agent simulations. Grids are often used for regular discretization of continuous space. Many methods exist for trajectory (path) planning on grids, we address the well known A* algorithm and the state-of-the-art Theta* algorithm. Theta* algorithm, as opposed to A*, provides 'any-angle' paths that look more realistic. In this paper, we provide an extension of both these algorithms to enable support for speed limit constraints. We experimentally evaluate and thoroughly discuss how the extensions affect the planning process showing reasonability and justification of our approach.
AB - Trajectory (path) planning is a well known and thoroughly studied field of automated planning. It is usually used in computer games, robotics or autonomous agent simulations. Grids are often used for regular discretization of continuous space. Many methods exist for trajectory (path) planning on grids, we address the well known A* algorithm and the state-of-the-art Theta* algorithm. Theta* algorithm, as opposed to A*, provides 'any-angle' paths that look more realistic. In this paper, we provide an extension of both these algorithms to enable support for speed limit constraints. We experimentally evaluate and thoroughly discuss how the extensions affect the planning process showing reasonability and justification of our approach.
KW - Speed limit constraints
KW - Theta
KW - Trajectory planning A
UR - http://www.scopus.com/inward/record.url?scp=79956074431&partnerID=8YFLogxK
U2 - 10.3233/978-1-60750-754-3-60
DO - 10.3233/978-1-60750-754-3-60
M3 - Conference contribution
AN - SCOPUS:79956074431
SN - 9781607507536
VL - 227
T3 - Frontiers in Artificial Intelligence and Applications
SP - 60
EP - 69
BT - Eleventh Scandinavian Conference on Artificial Intelligence
PB - IOS Press
ER -