Our First Paper!

On Wednesday, May 30th, Professor Giamou and Ethan Sequiera presented ARCO Lab’s first completely homegrown paper at the 21st Conference on Robots and Vision at The University of Guelph! We formulated the optimal placement of ranging beacons in a robot’s environment as a set function maximization problem. This allowed us to use an efficient greedy algorithm with suboptimality performance guarantees. With help from coauthors Hussein Saad and Professor Stephen Kelly, we compared our approach to a number of benchmarks, including an evolutionary optimization strategy. Check out the paper for details!