This paper presents two rehabilitation schemes for patients with upper limb impairments. The first is an active-assistive scheme based on the trajectory tracking of predefined paths in Cartesian space. In it, the system allows for an adjustable degree of variation with respect to ideal tracking. The amount of variation is determined through an admittance function that depends on the opposition forces exerted on the system by the user, due to possible impairments. The coefficients of the function allow the adjustment of the degree of assistance the robot will provide in order to complete the target trajectory. The second scheme corresponds to active movements in a constrained space. Here, the same admittance function is applied; however, in this case, it is unattached to a predefined trajectory and instead connected to one generated in real time, according to the user's intended movements. This allows the user to move freely with the robot in order to track a given path. The free movement is bounded through the use of virtual walls that do not allow users to exceed certain limits. A human-machine interface was developed to guide the robot's user.

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This article exploits a bio-inspired sensor technology named artificial electric-sense to emulate underwater pre-touch. The sensor is considered as an electric finger controlled remotely by an operator to follow the boundaries of objects. Using electric measurements only, the approach feeds back pre-touch forces and torques to the operator through an haptic interface. These forces and torques are generated by a set of virtual electric charges and dipoles arranged on the probe and reacting in the electric field reflected by the objects. This model of emulated forces is passive and guarantees the stability of a position–position haptic feedback loop. The whole approach is assessed through a set of experiments carried out on a Cartesian slave robot coupled to an haptic interface. The obtained results show the feasibility of the concept and its robustness to different configurations of objects. Such an electro-haptic feedback opens new perspectives in both electric field sensing and underwater robotics.