In this paper we present an experimental evaluation of automatic robotic assembly of complex planar parts. The torque-controlled DLR light-weight robot, equipped with an on-board camera (eye-in-hand configuration), is committed with the task of looking for given parts on a table, picking them, and inserting them inside the corresponding holes on a movable plate. Visual servoing techniques are used for fine positioning over the selected part/hole, while insertion is based on active compliance control of the robot and robust assembly planning in order to align the parts automatically with the hole. Execution of the complete task is validated through extensive experiments, and performance of humans and robot are compared in terms of overall execution time.

We first review research results of camera self-calibration achieved in photogrammetry, robotics and computer vision. Then we propose a method for self-calibration of robotic hand cameras by means of active motion. Through tracking a set of world points of unknown coordinates during robot motion, the internal parameters of the cameras (including distortions), the mounting parameters as well as the coordinates of the world points are estimated. The approach is fully autonomous, in that no initial guesses of the unknown parameters are to be provided from the outside by humans for the solution of a set of nonlinear equations. Sufficient conditions for a unique solution are derived in terms of controlled motion sequences. Methods to improve accuracy and robustness are proposed by means of best model identification and motion planning. Experimental results in both a simulated and a real environments are reported.

In this paper we propose a method for self-calibration of robotic hand cameras by means of active motion of the robot. Through tracking a set of world points of unknown coordinates, the internal parameters of the cameras (including lens distortions), the mounting parameters as well as the coordinates of the world points are estimated. The approach is fully autonomous, in that no initial guesses of the unknown parameters are to be provided from the outside by humans for the solution of a set of nonlinear equations. Sufficient conditions for a unique solution are derived in terms of controlled motion sequences. To improve robustness of the calibration, we propose to identify the best lens-distortion model by using F-test. Furthermore, a method is proposed to minimize the effect of robot motion uncertainties by motion planning. Experimental results in both a simulated and a real environments are reported.

We propose the so-called TeleSensor programming concept that uses sensory perception to achieve local autonomy in robotic manipulation. Sensor based robot tasks are used to define elemental moves within a high level programming environment. This approach is applicable in both, the real robot's world and the simulated one. Beside the graphical off-line programming concept, the range of application lies especially in the field of teleoperation with large time delays. A shared autonomy concept is proposed that distributes intelligence between man and machine. The feasibility of graphically simulating the robot within its environment is extended by emulating different sensor functions to achieve a correct copy of the real system behaviour as far as possible. The programming paradigm is supported by a sophisticated graphical man machine interface. Sensor fusion aspects with respect to autonomous sensor controlled task execution are discussed as well as the interaction between the real and the simulated system.>

The method of Fourier descriptors is extended to produce a set of normalized coefficients which are invariant under any affine transformation (translation, rotation, scaling, and shearing). The method is based on a parameterized boundary description which is transformed to the Fourier domain and normalized there to eliminate dependencies on the affine transformation and on the starting point. Invariance to affine transforms allows considerable robustness when applied to images of objects which rotate in all three dimensions, as is demonstrated by processing silhouettes of aircraft maneuvering in three-space.>