Robust Feature Selection and Correspondence for Visual Control of Robots

Stable correspondence-free image-based visual servoing is a challenging and important problem.

In classical image-based visual controllers, explicit feature correspondence (matching) to some desired arrangement (configuration) is required before a control input is obtained. Instead, this project will investigate variable feature correspondence and robust feature selection to simultaneously solve visual servoing problem, removing any feature tracking requirement or additional image processing.

Example of recent past work.

Chief Investigators