Home/Efficient C-Space and Cost Function Updates in 3D for Unmanned Aerial Vehicles

Efficient C-Space and Cost Function Updates in 3D for Unmanned Aerial Vehicles

Sebastian Scherer, David Ferguson and Sanjiv Singh
Conference Paper, Proceedings International Conference on Robotics and Automation, pp. 2049 – 2054, May, 2009

View Publication

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.


When operating in partially-known environments, autonomous vehicles must constantly update their maps and plans based on new sensor information. Much focus has been placed on developing efficient incremental planning algorithms that are able to efficiently replan when the map and associated cost function changes. However, much less attention has been placed on efficiently updating the cost function used by these planners, which can represent a significant portion of the time spent replanning. In this paper, we present the Limited Incremental Distance Transform algorithm, which can be used to efficiently update the cost function used for planning when changes in the environment are observed. Using this algorithm it is possible to plan paths in a completely incremental way starting from a list of changed obstacle classifications. We present results comparing the algorithm to the Euclidean distance transform and a mask-based incremental distance transform algorithm. Computation time is reduced by an order of magnitude for a UAV application. We also provide example results from an autonomous micro aerial vehicle with on-board sensing and computing.

author = {Sebastian Scherer and David Ferguson and Sanjiv Singh},
title = {Efficient C-Space and Cost Function Updates in 3D for Unmanned Aerial Vehicles},
booktitle = {Proceedings International Conference on Robotics and Automation},
year = {2009},
month = {May},
pages = {2049 – 2054},
keywords = {UAV,MAV, Planning. C-Space Expansion, Cost function, obstacle avoidance},
} 2018-10-04T15:26:36-04:00