This paper presents a mobile manipulation platform designed for autonomous depalletizing tasks. The proposed solution integrates machine vision, control and mechanical components to increase flexibility and ease of deployment in industrial environments such as warehouses. A collaborative robot mounted on a mobile base is proposed, equipped with a simple manipulation tool and a 3D in-hand vision system that detects parcel boxes on a pallet, and that pulls them one by one on the mobile base for transportation. The robot setup allows to avoid the cumbersome implementation of pick-and-place operations, since it does not require lifting the boxes. The 3D vision system is used to provide an initial estimation of the pose of the boxes on the top layer of the pallet, and to accurately detect the separation between the boxes for manipulation. Force measurement provided by the robot together with admittance control are exploited to verify the correct execution of the manipulation task. The proposed system was implemented and tested in a simplified laboratory scenario and the results of experimental trials are reported.

Continuum parallel robots ( CPRs ) comprise several flexible beams connected in parallel to an end-effector. They combine the inherent compliance of continuum robots with the high payload capacity of parallel robots. Workspace characterization is a crucial point in the performance evaluation of CPRs . In this paper, we propose a methodology for the workspace evaluation of planar continuum parallel robots ( PCPRs ), with focus on the constant-orientation workspace. An explorative algorithm, based on the iterative solution of the inverse geometrico-static problem is proposed for the workspace computation of a generic PCPR . Thanks to an energy-based modelling strategy, and derivative approximation by finite differences, we are able to apply the Kantorovich theorem to certify the existence, uniqueness, and convergence of the solution of the inverse geometrico-static problem at each step of the procedure. Three case studies are shown to demonstrate the effectiveness of the proposed approach.

In this paper, a mobile manipulation system for automatized logistic applications is presented. The robotic system is specifically designed for depalletizing/palletizing tasks, namely is product extraction from homogeneous pallets and assembly of new heterogeneous pallets. The robotic system is mainly composed by an autonomous vehicle, a collaborative robotic arm and a lifting device, which is able to collect products from different pallet layers. The handling strategy is not based on lifting items, as in classical pick-and-place operations, but on dragging them aboard the mobile vehicle. As the payload weight is not supported by the arm, the overall robotic system is very light compared to the manipulated items, which is a paramount benefit for a mobile collaborative application. This paper presents the mechanical design, the hardware selection and the experimentation in a laboratory scenario, thus demonstrating the effectiveness of the proposed manipulation strategy.

In this article, a new algorithm for the computation of workspace boundaries of continuum parallel robots (CPRs) is proposed. State-of-the-art techniques are mainly based on time-consuming joint space discretization approaches or task-space discretization algorithms, and only a few approaches are dedicated to the computation of workspace boundaries. The proposed approach for the computation of the workspace boundaries is based on (i) a free-space exploration strategy and (ii) a boundary reconstruction algorithm. The former is exploited to identify an initial workspace boundary location (exterior, interior boundaries, and holes), while the latter is used to reconstruct the complete boundary surface. Moreover, the algorithm is designed to be employed with CPR modeling strategies based on general discretization assumptions, in order to increase its applicability for various scopes. Our method is compared with two state-of-the-art algorithms in four cases studies, to validate the results and to establish its merits and limitations.