Cloud-Based Visually Aided Mobile Manipulator Kinematic Parameters Calibration

Mobile manipulators are often comprised of an extensive kinematic chain resulting from an industrial robot mounted on top of an autonomous mobile robot. In such a way, the system not only retains the parameters embedded in the two sub-systems, hence DH parameters for the industrial robot and odometry parameters for the mobile robot, but also includes the relative transformation between the two parts and an additional transformation for a camera mounted on the kinematic chain.In this complex setup, it is relatively simple to introduce kinematic inaccuracies, or in some cases, to operate the system in such a way that the kinematic parameters vary(e.g., rubber wheels on high payload).Estimating the values of such parameters might be too demanding for the on-board computing system.In this work, we propose a cloud-based visually aided parameter estimation method, which constantly receives data from the mobile manipulator and generates better estimates of the kinematic parameters through an UKF dual estimation.The overall system architecture is presented to the reader, together with the reasons for relying to a cloud based paradigm, for then giving a theoretical analysis and real world experiments and results.