Inter‐sample avoidance in trajectory optimizers using mixed‐integer linear programming

DOI10.1002/rnc.3101zbMath1316.90030OpenAlexW2097867042WikidataQ57591547 ScholiaQ57591547MaRDI QIDQ5254112

Oliver Turnbull, Arthur Richards

Publication date: 8 June 2015

Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/rnc.3101

zbMATH Keywords

mixed integer linear programmingtrajectory optimizationcollision avoidance

Mathematics Subject Classification ID

Mixed integer programming (90C11)

Related Items (5)

Trajectory planning for autonomous underwater vehicles in the presence of obstacles and a nonlinear flow field using mixed integer nonlinear programming ⋮ Robust intersample crossing of target sets with mixed‐integer linear programming ⋮ Integral reinforcement learning‐based approximate minimum time‐energy path planning in an unknown environment ⋮ Reduction in the number of binary variables for inter-sample avoidance in trajectory optimizers using mixed-integer linear programming ⋮ A line of sight constraint based on intermediary points for connectivity maintenance of multiagent systems using mixed-integer programming

Uses Software

• CPLEX

Cites Work

• Control of systems integrating logic, dynamics, and constraints
• On the use of mixed-integer linear programming for predictive control with avoidance constraints

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