Task-Specific Sensor Planning for Robotic Assembly Tasks
Name
multirobot_assembly.pdf
Description
Accepted version
Size
336.83 KB
Format
Adobe PDF
Checksum (MD5)
6131f9d966fc5d95c40163c21578d07e
Author(s)
Rosman, Guy
Choi, Changhyun
Dogar, Mehmet
Fisher IIIl, John W.
Rus, Daniela
Date Issued
May 2018
Publisher
IEEE
Citation
Rosman, Guy, Choi, Changhyun, Dogar, Mehmet, Fisher IIIl, John W. and Rus, Daniela. 2018. "Task-Specific Sensor Planning for Robotic Assembly Tasks."
Version
Author's final manuscript
Abstract
© 2018 IEEE. When performing multi-robot tasks, sensory feedback is crucial in reducing uncertainty for correct execution. Yet the utilization of sensors should be planned as an integral part of the task planning, taken into account several factors such as the tolerance of different inferred properties of the scene and interaction with different agents. In this paper we handle this complex problem in a principled, yet efficient way. We use surrogate predictors based on open-loop simulation to estimate and bound the probability of success for specific tasks. We reason about such task-specific uncertainty approximants and their effectiveness. We show how they can be incorporated into a multi-robot planner, and demonstrate results with a team of robots performing assembly tasks.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/icra.2018.8460194
