Trajectory Planning for Robots in Dynamic Human Environments

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Resumé

This paper present a trajectory planning algorithm
for a robot operating in dynamic human environments.
Environments such as pedestrian streets, hospital corridors and
train stations. We formulate the problem as planning a minimal
cost trajectory through a potential field, defined from the
perceived position and motion of persons in the environment. A
Rapidly-exploring Random Tree (RRT) algorithm is proposed
as a solution to the planning problem.
A new method for selecting the best trajectory in the RRT,
according to the cost of traversing a potential field, is presented.
The RRT expansion is enhanced to direct the search and
account for the kinodynamic robot constraints. Compared to
standard RRT, the algorithm proposed here find the robot
control input that will drive the robot towards a new sampled
point in the configuration space. The effect of the input is
simulated, to add a reachable vertex to the tree.
Instead of executing a whole trajectory, when planned, the
algorithm uses an Model Predictive Control (MPC) approach,
where only a short segment of the trajectory is executed while
a new iteration of the RRT is done.
The planning algorithm is demonstrated in a simulated
pedestrian street environment.
OriginalsprogEngelsk
TitelTrajectory Planning for Robots in Dynamic Human Environments : Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010)
Antal sider7
ForlagIEEE Press
Publikationsdato2010
Sider4293-4298
ISBN (Elektronisk)978-1-4244-6676-4
DOI
StatusUdgivet - 2010
NavnI E E E International Conference on Intelligent Robots and Systems. Proceedings
ISSN2153-0858

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Trajectories
Robots
Planning
Model predictive control
Costs

Citer dette

Svenstrup, M., Bak, T., & Andersen, H. J. (2010). Trajectory Planning for Robots in Dynamic Human Environments. I Trajectory Planning for Robots in Dynamic Human Environments: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010) (s. 4293-4298). IEEE Press. I E E E International Conference on Intelligent Robots and Systems. Proceedings https://doi.org/10.1109/IROS.2010.5651531
Svenstrup, Mikael ; Bak, Thomas ; Andersen, Hans Jørgen. / Trajectory Planning for Robots in Dynamic Human Environments. Trajectory Planning for Robots in Dynamic Human Environments: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010). IEEE Press, 2010. s. 4293-4298 (I E E E International Conference on Intelligent Robots and Systems. Proceedings).
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title = "Trajectory Planning for Robots in Dynamic Human Environments",
abstract = "This paper present a trajectory planning algorithmfor a robot operating in dynamic human environments.Environments such as pedestrian streets, hospital corridors andtrain stations. We formulate the problem as planning a minimalcost trajectory through a potential field, defined from theperceived position and motion of persons in the environment. ARapidly-exploring Random Tree (RRT) algorithm is proposedas a solution to the planning problem.A new method for selecting the best trajectory in the RRT,according to the cost of traversing a potential field, is presented.The RRT expansion is enhanced to direct the search andaccount for the kinodynamic robot constraints. Compared tostandard RRT, the algorithm proposed here find the robotcontrol input that will drive the robot towards a new sampledpoint in the configuration space. The effect of the input issimulated, to add a reachable vertex to the tree.Instead of executing a whole trajectory, when planned, thealgorithm uses an Model Predictive Control (MPC) approach,where only a short segment of the trajectory is executed whilea new iteration of the RRT is done.The planning algorithm is demonstrated in a simulatedpedestrian street environment.",
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Svenstrup, M, Bak, T & Andersen, HJ 2010, Trajectory Planning for Robots in Dynamic Human Environments. i Trajectory Planning for Robots in Dynamic Human Environments: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010). IEEE Press, I E E E International Conference on Intelligent Robots and Systems. Proceedings, s. 4293-4298. https://doi.org/10.1109/IROS.2010.5651531

Trajectory Planning for Robots in Dynamic Human Environments. / Svenstrup, Mikael; Bak, Thomas; Andersen, Hans Jørgen.

Trajectory Planning for Robots in Dynamic Human Environments: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010). IEEE Press, 2010. s. 4293-4298 (I E E E International Conference on Intelligent Robots and Systems. Proceedings).

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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N2 - This paper present a trajectory planning algorithmfor a robot operating in dynamic human environments.Environments such as pedestrian streets, hospital corridors andtrain stations. We formulate the problem as planning a minimalcost trajectory through a potential field, defined from theperceived position and motion of persons in the environment. ARapidly-exploring Random Tree (RRT) algorithm is proposedas a solution to the planning problem.A new method for selecting the best trajectory in the RRT,according to the cost of traversing a potential field, is presented.The RRT expansion is enhanced to direct the search andaccount for the kinodynamic robot constraints. Compared tostandard RRT, the algorithm proposed here find the robotcontrol input that will drive the robot towards a new sampledpoint in the configuration space. The effect of the input issimulated, to add a reachable vertex to the tree.Instead of executing a whole trajectory, when planned, thealgorithm uses an Model Predictive Control (MPC) approach,where only a short segment of the trajectory is executed whilea new iteration of the RRT is done.The planning algorithm is demonstrated in a simulatedpedestrian street environment.

AB - This paper present a trajectory planning algorithmfor a robot operating in dynamic human environments.Environments such as pedestrian streets, hospital corridors andtrain stations. We formulate the problem as planning a minimalcost trajectory through a potential field, defined from theperceived position and motion of persons in the environment. ARapidly-exploring Random Tree (RRT) algorithm is proposedas a solution to the planning problem.A new method for selecting the best trajectory in the RRT,according to the cost of traversing a potential field, is presented.The RRT expansion is enhanced to direct the search andaccount for the kinodynamic robot constraints. Compared tostandard RRT, the algorithm proposed here find the robotcontrol input that will drive the robot towards a new sampledpoint in the configuration space. The effect of the input issimulated, to add a reachable vertex to the tree.Instead of executing a whole trajectory, when planned, thealgorithm uses an Model Predictive Control (MPC) approach,where only a short segment of the trajectory is executed whilea new iteration of the RRT is done.The planning algorithm is demonstrated in a simulatedpedestrian street environment.

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Svenstrup M, Bak T, Andersen HJ. Trajectory Planning for Robots in Dynamic Human Environments. I Trajectory Planning for Robots in Dynamic Human Environments: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010). IEEE Press. 2010. s. 4293-4298. (I E E E International Conference on Intelligent Robots and Systems. Proceedings). https://doi.org/10.1109/IROS.2010.5651531