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Optimal task allocation and dynamic trajectory planning for multi-vehicle systems using nonlinear hybrid optimal control

Glocker, Markus and Reinl, Christian and Stryk, Oskar von (2006):
Optimal task allocation and dynamic trajectory planning for multi-vehicle systems using nonlinear hybrid optimal control.
In: Proc. 1st IFAC-Symposium on Multivehicle Systems, Salvador, Brazil, In: 1st IFAC-Symposium on Multivehicle Systems, Salvador, Brazil, [Conference or Workshop Item]

Abstract

Based on a nonlinear hybrid dynamical systems model a new planning method for optimal coordination and control of multiple unmanned vehicles is investigated. The time dependent hybrid state of the overall system consists of discrete (roles, actions) and continuous (e.g. position, orientation, velocity) state variables of the vehicles involved. The evolution in time of the system’s hybrid state is described by a hybrid state automaton. The presented approach enables a tight and formal coupling of discrete and continuous state dynamics, i.e. of dynamic role and action assignment and sequencing as well as of the physical motion dynamics of a single vehicle modeled by nonlinear differential equations. The planning problem of determining optimal hybrid state trajectories that minimize a cost function as time or energy for optimal multi-vehicle cooperation subject to constraints including the vehicle’s motion dynamics is transformed to a mixed-binary dynamic optimization problem being solved numerically. The numerical method consists of an inner iteration where multiphase optimal control problems are solved using a direct collocation method and an outer iteration based on a branch-and-bound search of the discrete solution space. The approach presented in this paper is applied to the scenarios of optimal simultaneous waypoint or target sequencing and dynamic trajectory planning for a team of unmanned aerial vehicles in a plane and to optimal role assignment and physics-based trajectories in robot soccer.

Item Type: Conference or Workshop Item
Erschienen: 2006
Creators: Glocker, Markus and Reinl, Christian and Stryk, Oskar von
Title: Optimal task allocation and dynamic trajectory planning for multi-vehicle systems using nonlinear hybrid optimal control
Language: English
Abstract:

Based on a nonlinear hybrid dynamical systems model a new planning method for optimal coordination and control of multiple unmanned vehicles is investigated. The time dependent hybrid state of the overall system consists of discrete (roles, actions) and continuous (e.g. position, orientation, velocity) state variables of the vehicles involved. The evolution in time of the system’s hybrid state is described by a hybrid state automaton. The presented approach enables a tight and formal coupling of discrete and continuous state dynamics, i.e. of dynamic role and action assignment and sequencing as well as of the physical motion dynamics of a single vehicle modeled by nonlinear differential equations. The planning problem of determining optimal hybrid state trajectories that minimize a cost function as time or energy for optimal multi-vehicle cooperation subject to constraints including the vehicle’s motion dynamics is transformed to a mixed-binary dynamic optimization problem being solved numerically. The numerical method consists of an inner iteration where multiphase optimal control problems are solved using a direct collocation method and an outer iteration based on a branch-and-bound search of the discrete solution space. The approach presented in this paper is applied to the scenarios of optimal simultaneous waypoint or target sequencing and dynamic trajectory planning for a team of unmanned aerial vehicles in a plane and to optimal role assignment and physics-based trajectories in robot soccer.

Title of Book: Proc. 1st IFAC-Symposium on Multivehicle Systems
Place of Publication: Salvador, Brazil
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Simulation, Systems Optimization and Robotics Group
Event Title: 1st IFAC-Symposium on Multivehicle Systems
Event Location: Salvador, Brazil
Date Deposited: 09 Jul 2019 10:00
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