Every year the shortage of biosamples is increasing, while the requirements for their quality are constantly tightening, which requires the introduction of new technological solutions. To solve these problems, a robotic system for aliquoting biological liquid was developed. The aliquotation process is described. The station includes a serial robot on which a gripper based on a globoid worm is installed. The gripping device is parameterized and takes into account the gripping force for different finger deflections. 3D models were developed using Computer Aided Design (CAD) system tools, after which working layouts were created using 3D printing. The design process and test results are discussed to show the efficiency of the built prototype with lab tests.

In this paper, we investigate dynamic walking as a convergence to the system's own limit cycles, not to artificially generated trajectories, which is one of the lessons in the concept of passive dynamic walking. For flexible walking, gait transitions can be performed by moving from one limit cycle to another one, and thus, the flexibility depends on the range in which limit cycles exist. To design a bipedal walker based on this approach, we explore period-1 passive limit cycles formed by natural dynamics and analyze them. We use a biped model with knees and point feet to perform numerical simulations by changing the center of mass locations of the legs. As a result, we obtain mass distributions for the maximum flexibility, which can be attained from very limited location sets. We discuss the effect of parameter variations on passive dynamic walking and how to improve robot design by analyzing walking performance. Finally, we present a practical application to a real bipedal walker, designed to exhibit more flexible walking based on this study.

In the past years a large number of new surgical devices have been developed to improve the operation outcomes and reduce the patient's trauma. Nevertheless, the dexterity and accuracy required in positioning the surgical tools are often unreachable if the surgeons are not assisted by a suitable system. Since a medical robot works in an operating room, close to the patient and the medical staff, it has to satisfy much stricter requirements with respect to an industrial one. From a kinematic point of view, the robot must reach any target position in the patient's body, being as less invasive as possible for the surgeon's workspace. In order to meet such requirements, the right robot structure has to be chosen by means of the definition of suitable kinematic performance indices.

In this paper some task-based indices based on the robot workspace and stiffness are presented and discussed. The indices will be used in a multiobjective optimization problem to evaluate best robot kinematic structure for a given neurosurgical task.

The paper describes a skiing robot that is capable of skiing autonomously on a ski slope. The robot uses carving skiing technique. Based on a complex sensory system it is capable of autonomously navigating on the ski slope, avoiding obstacles, and maintaining a stable position during skiing on an unknown ski slope. The robot was tested using simulation in a virtual reality environment as well as on a ski slope.