Global Optimization Techniques in Camera and Robot Calibration PhD Thesis Proposal

The advantages of vision-guided robots are widely recognized in industry and any improvement in the field has a lagre practical impact. First, we present state of the art in globally optimal algorithms in computer vision. The main mathematical aproaches that can be noticed in the field are discussed: polynomial methods, quasi-convex optimization, branch-and-bound algorithm and convex relaxation schemes. Next, we review the problem of camera-robot calibration. The Hand-Eye and Robot-World calibrations are presented and the problem of vision-aided calibration is formulated. The main goal of the thesis is to apply and augment the methods of computer vision in the field of vision-aided robotics and to present a practical global optimization technique for vision-aided robot calibration.