Combining visual and force feedback for the precise robotic manipulation of bulky components

The increasing request of flexible robotic applications asks for systems more capable in perceiving and interacting with the environment, to adapt the robot behavior to possible changes. The challenge is the easy design of the robotic system around the application. This becomes crucial in particular when the objects to be manipulated are bulky, and the relative positions between the robot and the objects to be manipulated are uncertain and high precision is required to successfully complete a task. In this paper a possible guideline to design a system capable to localize itself, identify a target, bulky, object and manipulate it, is presented. Vision systems techniques and technologies are briefly analyzed in order to select the most suitable solution under restrictive constraints. The objects considered for this approach are indeed bulky, texture-less, without strong geometrical features, with uncertain positions and rotations in the 3D space and strict accuracy tolerances. Since the presented work involves object manipulation and assembly, also force feedback is necessary when interaction is involved. This allows the robot to perceive the interacting environment through touch and avoid possibly dangerous huge forces exchange. With this purpose, a method for tuning the impedance control parameters is derived, to keep interaction forces below maximum allowed values. The autonomous localization, grasping and assembly of a sidewall panel of an airplane is used as test. Such scenario involves different challenges for both the vision system and the manipulation, indeed the environment is very narrow and cluttered, lighting is variable, assembly tolerances are very tight (10 mm) considering huge objects (1000x1500 mm). Experiments show that the success rate of completing a task increases, combining vision perception and force control, with respect to the single use of visual localization and position control. The coupled action of these two techniques makes the entire application more reliable.