Fast Obstacle Avoidance Based on Real-Time Sensing
Name
Fast_Obstacle_Avoidance_Based_on_Real-Time_Sensing.pdf
Description
Published version
Size
6.33 MB
Format
Adobe PDF
Checksum (MD5)
409505006bf7d8027d88193edf018034
Author(s)
Huber, Lukas
Slotine, Jean-Jacques
Billard, Aude
Date Issued
March 2023
Journal
IEEE Robotics and Automation Letters
Publisher
Institute of Electrical and Electronics Engineers
Citation
L. Huber, J. -J. Slotine and A. Billard, "Fast Obstacle Avoidance Based on Real-Time Sensing," in IEEE Robotics and Automation Letters, vol. 8, no. 3, pp. 1375-1382, March 2023, doi: 10.1109/LRA.2022.3232271.
Version
Final published version
Abstract
Humans excel at navigating and moving through dynamic and complex spaces, such as crowded streets. For robots to do the same, it is crucial that they are endowed with highly reactive obstacle avoidance which is adept at partial and poor sensing. We address the issue of enabling obstacle avoidance based on sparse and asynchronous perception. The proposed control scheme combines a high-level input command provided by either a planner or a human operator with fast reactive obstacle avoidance (FOA). The sampling-based sensor data can be combined with an analytical reconstruction of the obstacles for real-time collision avoidance. Thus, we can ensure that the agent does not become stuck when a feasible path exists between obstacles. Our algorithm was evaluated experimentally on static laser data from cluttered, indoor office environments. Additionally, it was used in shared-control mode in a dynamic and complex outdoor environment in the center of Lausanne. The proposed control scheme successfully avoided collisions in both scenarios. During the experiments, the controller took 1 ms to evaluate over 30000 data points.
MIT Department
Massachusetts Institute of Technology. Nonlinear Systems Laboratory
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/lra.2022.3232271
