Abstract
Open-ended human environments, such as pedestrian streets, hospital corridors, train stations etc., are places where robots start to emerge. Hence, being able to plan safe
and natural trajectories in these dynamic environments is an important skill for future generations of robots. In this work the problem is formulated as planning a minimal cost trajectory through a potential field, defined from the perceived position and motion of persons in the environment. A modified Rapidlyexploring Random Tree (RRT) algorithm is proposed as a
solution to the planning problem.
The algorithm implements a new method for selecting the best trajectory in the RRT, according to the cost of traversing a potential field. Furthermore the RRT expansion is enhanced to direct the search and account for the kinodynamic robot constraints. A model predictive control (MPC) approach is taken to accommodate for the uncertainty in the dynamic environment.
The planning algorithm is demonstrated in a simulated pedestrian street environment.
and natural trajectories in these dynamic environments is an important skill for future generations of robots. In this work the problem is formulated as planning a minimal cost trajectory through a potential field, defined from the perceived position and motion of persons in the environment. A modified Rapidlyexploring Random Tree (RRT) algorithm is proposed as a
solution to the planning problem.
The algorithm implements a new method for selecting the best trajectory in the RRT, according to the cost of traversing a potential field. Furthermore the RRT expansion is enhanced to direct the search and account for the kinodynamic robot constraints. A model predictive control (MPC) approach is taken to accommodate for the uncertainty in the dynamic environment.
The planning algorithm is demonstrated in a simulated pedestrian street environment.
| Bidragets oversatte titel | Sampling Baseret Trajektorie Planlægning for Robotter i Dynamiske Mennesklige Miliøer |
|---|---|
| Originalsprog | Engelsk |
| Titel | Proceedings of Robotics : Science and Systems 2010, Workshop: Motion Planning: From Theory to Practice |
| Publikationsdato | 27 jun. 2010 |
| Status | Udgivet - 27 jun. 2010 |