The way an object is released by the passer to a partner is fundamental for the success of the handover and for the experienced fluency and quality of the interaction. Nonetheless, although its apparent simplicity, object handover involves a complex combination of predictive and reactive control mechanisms that were not fully investigated so far. Here, we show that passers use visual-feedback based anticipatory control to trigger the beginning of the release, to launch the appropriate motor program, and adapt such predictions to different speeds of the receiver’s reaching out movements. In particular, the passer starts releasing the object in synchrony with the collision with the receiver, regardless of the receiver’s speed, but the passer’s speed of grip force release is correlated with receiver speed. When visual feedback is removed, the beginning of the passer’s release is delayed proportionally with the receiver’s reaching out speed; however, the correlation between the passer’s peak rate of change of grip force is maintained. In a second study with 11 participants receiving an object from a robotic hand programmed to release following stereotypical biomimetic profiles, we found that handovers are experienced as more fluent when they exhibit more reactive release behaviours, shorter release durations, and shorter handover durations. The outcomes from the two studies contribute understanding of the roles of sensory input in the strategy that empower humans to perform smooth and safe handovers, and they suggest methods for programming controllers that would enable artificial hands to hand over objects with humans in an easy, natural and efficient way.

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Testing and characterization of Micro-Electro-Mechanical Systems (MEMS) and Micro-Opto-Electro-Mechanical Systems (MOEMS) can be very challenging due to the multi-domain nature of these devices. Nowadays high volume, high-cost, and accurate measuring systems are necessary to characterize and test MEMS and MOEMS especially to examine motions, deflections and resonance frequencies. This paper presents a fast-developing and low-cost environment for MEMS and MOEMS testing and characterization. The environment is based on a flexible mixed-signal platform, named ISIF (Intelligent Sensor InterFace). As a case study we consider the characterization of a double axis scanning micromirror. The testing environment has been validated by comparing measurement results with results obtained by Finite Element Method simulation performed with Comsol MultiphysicsTM. Finally, these results have been used to create an electrical equivalent model of the micromirror

Since there still is a lack of autonomous solutions in the S&R field, in the NBC one and more in general when a manipulation of dangerous substances is requested, technical solutions are mainly approaching these problems with teleoperation. This paper describes a particular specific system control architecture suitable for remotely operated platforms for S&R, IED-EOD and NBC applications. The proposed architecture is described, a realized prototype is presented and on field results gathered in real applications, validating the solution, are discussed.

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