2017, Decentralized Navigation of Quad-copters while avoiding static and dynamic obstacles using MPC

In this project, a predcitive control scheme is derived for the navigation of multiple quadrotors in the constraint environment based on the quadrotor’s model obtained using Newton-Euler method. Nonlinear model predictive control problem is first formulated for the decentralized and autonomous navigation of multiple quadcopters subject to constraints. The constraints are in the form of static and dynamic obstacle avoidance, and limits on the states and inputs. The static and dynamic obstacle are modeled as sphere while formulating Nonlinear MPC problem. The quad-rotor model is then linearized and system is converted to mixed logical dynamical (MLD) system which is described by the linear dynamical equations subject to linear constraints involving real and logical variable. The hybrid MPC poblem is then formulated subject to MLDs, where the constraints are linear and obstacles are modeled as poy-hedral sets. The performance of, NMPC is analyzed through simulation and MPC scheme is analyzed by simulation and verified by performing indoor experiments.