The International Conference on Intelligent Robots and Systems (known as IROS) recently accepted the paper Adaptive Informative Sampling with Environment Partitioning for Heterogeneous Multi-Robot Systems submitted by four MRSD alumni from the graduating Class of 2020. Team G, comprised of Yunfei Shi, Ning Wang, Yang Zhang, & Jianmin Zheng, worked hard for all of 2019 on their group project, “Autonomous Modeling Solution” mentored by Professor Katia Sycara. When the class ended in early December, they improved their sampling algorithm and continued to refine their work. They proposed a novel strategy that utilizes the heterogeneous capabilities of the robot fleet to perform efficient information gathering tasks. The algorithm was then validated on their modular-designed multi-robot informative sampling system developed as their group project. This system can be used in various environmental modeling tasks including monitoring the thermal mapping of a wildfire-affected area.
