TY - GEN
T1 - Mathematical programming for multi-vehicle motion planning problems
AU - Abichandani, Pramod
AU - Ford, Gabriel
AU - Benson, Hande Y.
AU - Kam, Moshe
N1 - Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - Real world Multi-Vehicle Motion Planning (MVMP) problems require the optimization of suitable performance measures under an array of complex and challenging constraints involving kinematics, dynamics, communication connectivity, target tracking, and collision avoidance. The general MVMP problem can thus be formulated as a mathematical program (MP). In this paper we present a mathematical programming (MP) framework that captures the salient features of the general MVMP problem. To demonstrate the use of this framework for the formulation and solution of MVMP problems, we examine in detail four representative works and summarize several other related works. As MP solution algorithms and associated numerical solvers continue to develop, we anticipate that MP solution techniques will be applied to an increasing number of MVMP problems and that the framework and formulations presented in this paper may serve as a guide for future MVMP research.
AB - Real world Multi-Vehicle Motion Planning (MVMP) problems require the optimization of suitable performance measures under an array of complex and challenging constraints involving kinematics, dynamics, communication connectivity, target tracking, and collision avoidance. The general MVMP problem can thus be formulated as a mathematical program (MP). In this paper we present a mathematical programming (MP) framework that captures the salient features of the general MVMP problem. To demonstrate the use of this framework for the formulation and solution of MVMP problems, we examine in detail four representative works and summarize several other related works. As MP solution algorithms and associated numerical solvers continue to develop, we anticipate that MP solution techniques will be applied to an increasing number of MVMP problems and that the framework and formulations presented in this paper may serve as a guide for future MVMP research.
UR - http://www.scopus.com/inward/record.url?scp=84864472100&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84864472100&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2012.6225141
DO - 10.1109/ICRA.2012.6225141
M3 - Conference contribution
AN - SCOPUS:84864472100
SN - 9781467314039
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 3315
EP - 3322
BT - 2012 IEEE International Conference on Robotics and Automation, ICRA 2012
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2012 IEEE International Conference on Robotics and Automation, ICRA 2012
Y2 - 14 May 2012 through 18 May 2012
ER -