Dynamic Risk Density for Autonomous Navigation in Cluttered Environments without Object Detection
Name
pierson2019icra.pdf
Description
Accepted version
Size
2.67 MB
Format
Adobe PDF
Checksum (MD5)
b556254fc027c60da0822a27f4940fa6
Author(s)
Pierson, Alyssa
Vasile, Cristian-Ioan
Gandhi, Anshula
Schwarting, Wilko
Karaman, Sertac
Rus, Daniela L.
Date Issued
August 2019
Journal
2019 International Conference on Robotics and Automation
Publisher
IEEE
Citation
Pierson, Alyssa et al. "Dynamic Risk Density for Autonomous Navigation in Cluttered Environments without Object Detection." 2019 International Conference on Robotics and Automation (ICRA), May 2019, Montreal, Canada, Institute of Electrical and Electronics Engineers (IEEE), 2019.
Version
Author's final manuscript
Abstract
In this paper, we examine the problem of navigating cluttered environments without explicit object detection and tracking. We introduce the dynamic risk density to map the congestion density and spatial flow of the environment to a cost function for the agent to determine risk when navigating that environment. We build upon our prior work, wherein the agent maps the density and motion of objects to an occupancy risk, then navigate the environment over a specified risk level set. Here, the agent does not need to identify objects to compute the occupancy risk, and instead computes this cost function using the occupancy density and velocity fields around them. Simulations show how this dynamic risk density encodes movement information for the ego agent and closely models the object-based congestion cost. We implement our dynamic risk density on an autonomous wheelchair and show how it can be used for navigating unstructured, crowded and cluttered environments. Keywords: Navigation; Cost function; Wheelchairs; Dynamics; Vehicle dynamics; Planning; Level set
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/icra.2019.8793813
