NDLI: UAVs Trajectory Planning by Distributed MPC under Radio Communication Path Loss Constraints

Content Provider	Springer Nature Link
Author	Grøtli, Esten Ingar Grancharova, Alexandra Ho, Dac Tu Johansen, Tor Arne
Copyright Year	2014
Abstract	In this paper, a distributed linear MPC approach to solve the trajectory planning problem for rotary-wing UAVs is proposed, where the objective of the UAV system is to form a communication network to multiple targets with given radio communication capacities. The approach explicitly incorporates constraints on radio communication path losses, computed by using SPLAT! that is able to take into account terrain models and antenna locations. In order to enhance the online optimization, at each time sample the terrain below each UAV and the communication path losses are approximated with linear functions of the spatial coordinates. This leads to linear MPC sub-problems, which are solved by using convex quadratic programming. An algorithm for automatic initialization and optimal reconfiguration of the communication topology in case of failures or severe radio path loss due to e.g. channel fading, is proposed. The communication network that is provided by the UAVs is considered to be a payload communication capacity that is normally independent of the command and control datalink used to control the UAVs. The performance of the distributed linear MPC trajectory planning and the reconfiguration algorithm is studied on two simulation cases with four UAVs and two targets.
Ending Page	134
Page Count	20
Starting Page	115
File Format	PDF
ISSN	09210296
e-ISSN	15730409
Journal	Journal of Intelligent & Robotic Systems
Issue Number	1
Volume Number	79
Language	English
Publisher	Springer Netherlands
Publisher Date	2014-08-16
Publisher Place	Dordrecht
Access Restriction	Subscribed
Subject Keyword	Automated systems (robots, etc.) Robotics Trajectory planning Constraints Control, Robotics, Mechatronics Radio-communication Distributed control Artificial Intelligence (incl. Robotics) Mechanical Engineering Multi-vehicle coordination Autonomous vehicles Predictive control Electrical Engineering
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Artificial Intelligence Control and Systems Engineering Mechanical Engineering Electrical and Electronic Engineering Software

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