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Project

Combined Learning, Planning and Control for Optimal Navigation in Uncertain Environments

This research focuses on novel methods to improve the efficiency of navigation in uncertain environments by combining learning techniques, including optimal experiment design ideas, and optimal path/trajectory planning. Learning aims at reducing uncertainty, in order to improve the performance of the planner, and this at the cost of temporarily suboptimal motion. Application: drones.

Date:16 Sep 2019 →  16 Jul 2023
Keywords:Control Engineering, Robotics, Automation
Disciplines:Control engineering, Design theories and methods not elsewhere classified, Robotics and automatic control, Computer theory not elsewhere classified
Project type:PhD project