Convex Optimization for Trajectory Generation: A Tutorial on Generating Dynamically Feasible Trajectories Reliably and Efficiently

doi:10.1109/MCS.2022.3187542

Convex Optimization for Trajectory Generation: A Tutorial on Generating Dynamically Feasible Trajectories Reliably and Efficiently

2022-10-01

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DOI：10.1109/MCS.2022.3187542

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Autonomous vehicles and robots promise many exciting new applications that will transform society. For example, autonomous aerial vehicles (AAVs) operating in urban environments could deliver commercial goods and emergency medical supplies, monitor traffic, and provide threat alerts for national security [1]. At the same time, these applications present significant engineering challenges related to performance, trustworthiness, and safety. For instance, AAVs can be a catastrophic safety hazard should they lose control or situational awareness over a populated area. Space missions, self-driving cars, and applications of autonomous underwater vehicles share similar concerns.

Keywords:

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Urban areas

Optimal control

Tutorials

Transforms

Convex functions

Real-time systems

Convex Optimization for Trajectory Generation: A Tutorial on Generating Dynamically Feasible Trajectories Reliably and Efficiently

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