Manoharan, Amith (IIIT Delhi), Sharma, Rajnikant (University of Cincinnati), Sujit, P. B (IIITD)

Nonlinear Model Predictive Control to Aid Cooperative Localization

Scheduled for presentation during the Regular Session "Path Planning I" (WeA1), Wednesday, June 12, 2019, 11:00−11:20, Heritage B

2020 International Conference on Unmanned Aircraft Systems (ICUAS), June 11-14, 2019, Athens, Greece

This information is tentative and subject to change. Compiled on April 26, 2024

Abstract

This paper proposes a nonlinear model predictive control (NMPC) scheme to tackle the problem of localization and path planning of a group of unmanned aerial vehicles (UAVs) in global positioning system (GPS) denied environments. It is assumed that the UAVs can cooperate by sharing information among themselves. It is also assumed that the area under consideration contains some landmarks with known locations. The NMPC computes the optimal control inputs for the vehicles such that the vehicles cooperate to transit from a source location to a destination while choosing a path that will cover enough landmarks for localization. An Extended Kalman Filter (EKF) is used to estimate the vehicle positions using only relative bearing measurements. The efficacy of the proposed method was evaluated through numerical simulations, and the results are discussed.