Paper Info
Title
Trajectory planning for car-like robots in unknown, unstructured environments
Abstract
We describe a variable-velocity trajectory planning algorithm for navigating car-like robots through unknown, unstructured environments along a series of possibly corrupted GPS waypoints. The trajectories are guaranteed to be kine-matically feasible, i.e., they respect the robot's acceleration and deceleration capabilities as well as its maximum steering angle and steering rate. Their costs are computed using LiDAR and camera data and depend on factors such as proximity to obstacles, curvature, changes of curvature, and slope. In a second step, velocities for the least-cost trajectory are adjusted based on the dynamics of the vehicle. When the robot is faced with an obstacle on its trajectory, the planner is restarted to compute an alternative trajectory. Our algorithm is robust against GPS error and waypoints placed in obstacle-filled areas. It was successfully used at euRathlon 20131, where our autonomous vehicle MuCAR-3 took first place in the “Autonomous Navigation” scenario.
Year
DOI
Venue
2014
10.1109/IROS.2014.6943071
Intelligent Robots and Systems
Keywords
Field
DocType
Global Positioning System,cameras,mobile robots,optical radar,path planning,robot kinematics,steering systems,trajectory control,vehicle dynamics,GPS waypoints,LiDAR,autonomous navigation,autonomous vehicle MuCAR-3,camera data,car-like robots,least-cost trajectory,robot acceleration capabilities,robot deceleration capabilities,steering angle,steering rate,variable-velocity trajectory planning algorithm,vehicle dynamics
Computer vision,Robot control,Obstacle,Curvature,Computer science,Control engineering,Artificial intelligence,Acceleration,Global Positioning System,Robot,Trajectory,Error analysis for the Global Positioning System
Conference
ISSN
Citations 
PageRank 
2153-0858
1
0.40
References 
Authors
9
3
Name
Order
Citations
PageRank
Dennis Fassbender122.79
André Müller220.94
Hans-Joachim Wuensche38819.09