Guiding vector fields for robot motion control

Presented by

Weijia Yao (Ph.D.)

Guiding vector fields for robot motion control

University of Groningen

Groningen, the Netherlands

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Abstract

Using a designed vector field to guide robots to follow a given geometric desired path has found a range of practical applications, such as underwater pipeline inspection, warehouse navigation and highway traffic monitoring. It is thus in great need to build a rigorous theory to guide practical implementations with formal guarantees. It is even so when multiple robots are required to follow predefined desired paths or maneuver on surfaces and coordinate their motions to efficiently accomplish repetitive and laborious tasks.

In this talk, I will introduce guiding vector fields on a Euclidean space and a Riemannian manifold, for single-robot and multi-robot path following and motion coordination. A guiding vector field is generally composed of two terms: a convergence term which enables the integral curves of the vector field to converge to the desired path, and a propagation term which is tangent to the desired path such that movement along the desired path is ensured. Since the guiding vector field is not the gradient of any potential function, and also due to the existence of singular points where the vector field vanishes, the theoretical analysis becomes challenging. Therefore, I will present theoretical results, and elaborate on how to utilize guiding vector fields with variations in practical applications, including global robot navigation, collision avoidance and multi-robot motion coordination.

Presenter biography

Weijia Yao obtained the Ph.D. degree with distinction cum laude in systems and control theory from the University of Groningen, Groningen, the Netherlands, in 2021. He has published more than 20 peer-reviewed journal and conference papers in the robotics and automatic control fields, including IEEE Transactions on Robotics, IEEE Transactions on Automatic Control, IEEE Transactions on Intelligent Transportation Systems, Automatica, IEEE International Conference on Robotics and Automation (ICRA), IEEE Conference on Decision and Control (CDC). He was a finalist for the Best Conference Paper Award at ICRA in 2021, a finalist for the Georges Giralt PhD Award in 2022, the recipient of the Outstanding Master Degree Dissertation award of Hunan province, China, in 2020, and the champion of the technical challenge in 2019 RoboCup Middle Size League. His research interests include mobile robotics, multiagent systems and nonlinear systems and control.