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Sensor scheduling in mobile robots using incomplete information via Min-Conflict with Happiness
Aaron Gage1, Robin Roberson Murphy
1University of South Florida, Tampa, FL 33620, USA. agage@csee.usf.edu
Summary
This study introduces the Min-Conflict with Happiness (MCH) algorithm for mobile robot sensor allocation under uncertainty. MCH optimizes sensor certainty, improving assignment success and sensing utility compared to other methods.
Area of Science:
- Robotics
- Artificial Intelligence
- Sensor Networks
Background:
- Mobile robots require efficient sensor allocation for navigation and task completion.
- Incomplete information and resource contention pose significant challenges to sensor scheduling.
Purpose of the Study:
- To develop and apply a novel heuristic algorithm for sensor allocation in mobile robots with incomplete information.
- To optimize sensor certainty and improve the overall sensing utility for robots.
Main Methods:
- A variant of the Min-Conflict algorithm, termed Min-Conflict with Happiness (MCH), was developed.
- The algorithm was tested using simulation experiments and real-world data from Nomad200 robots with the SFX architecture.
Main Results:
- MCH satisfied up to 142% more sensor assignments than greedy or random methods.
- It achieved a 7-24% increase in overall sensing utility, even with sensor failures.
- MCH demonstrated support for behavioral sensor fusion and fast, dynamic schedule repair.
Conclusions:
- The Min-Conflict with Happiness algorithm offers a robust and efficient solution for sensor allocation in uncertain environments.
- MCH provides practical advantages, including computational efficiency, architectural compatibility, and minimal disruption to robot behaviors.