Implementation Regarding Publication "Fuzzy-Logic-based model predictive control: A paradigm integrating optimal and common-sense decision making"
The code in this repository is used to implement and test a new algorithm called FLMPC (Fuzzy logic based model predictive control). To find an optimal path in search and rescue for multi-robot systems, it is common to use MPC with stochastic cost functions. We decided to replace stochastic cost functions with fuzzy cost functions (the exact reasoning can be found in the paper (there is no DOI yet) ). In this repository, MPC with stochastic cost function, FLMPC and bi-level FLMPC have been implemented. This code generates simulations with people and obstacles. Robots are then spawned within them. The drones have no knowledge of the environment, but they can sense the environment around them, but the measurements are noisy. The task for the drones is to find people as quickly as possible. We published raw data in seperate repository (https://doi.org/10.4121/2479c468-624b-49b6-9e2e-63bd633c9bc2) because they were taking over 14 GB of disk space.