This paper presents the design and development of a robotic system to give physical assistance to the elderly or people with neurological disorders such as Ataxia or Parkin-son's. In particular, we propose using a mobile collaborative robot with an interaction-assistive whole-body interface to help people unable to maintain balance. The robotic system consists of an Omni-directional mobile base, a high-payload robotic arm, and an admittance-type interface acting as a support handle while measuring human-sourced interaction forces. The postural balance of the human body is estimated through the projection of the body Center of Mass (CoM) to the support polygon (SP) representing the quasi-static Center of Pressure (CoP). In response to the interaction forces and the tracking of the human posture, the robot can create assistive forces to restore balance in case of its loss. Otherwise, during normal stance or walking, it will follow the user with minimum/no opposing forces through the generation of coupled arm and base movements. As the balance-restoring strategy, we propose two strategies and evaluate them in a laboratory setting on healthy human participants. Quantitative and qualitative results of a 12-subjects experiment are then illustrated and discussed, comparing the performances of the two strategies and the overall system.

The emergence of new robotic technologies such as compliant control and soft robotics, has contributed to safe physical Human-Robot Interaction (pHRI) mainly for assistive applications. However, a robot capable of directly manipulating the human body, which is key for the implementation of autonomous rescue robots, has not been developed so far. In this paper, the development of a gripper and methods for the robotic manipulation of a laying victim's forearm, initiated by the robot is addressed, and validated based on experimental results. An underactuated gripper with added proprioceptive sensors has been designed, with environment sensing and tactile recognition capabilities. This method provides a stable grasping of a human forearm that lays on a surface and is capable of estimating the roll angle of the grasped arm for precise location and safe manipulation. The roll-angle estimation method is based on Machine Learning and has been trained with experimental data obtained from experiments with human volunteers. The resulting method provides robust and precise grasping, tolerant to location inaccuracy with inexpensive sensors. This is one of the very first works on the robotic human-body manipulation.

A new robotic system for Search And Rescue (SAR) operations based on the automatic wristband placement on the victims' arm, which may provide identification, beaconing and remote sensor readings for continuous health monitoring. This paper focuses on the development of the automatic target localization and the device placement using an unmanned aerial manipulator. The automatic wrist detection and localization system uses an RGB-D camera and a convolutional neural network based on the region faster method (Faster R-CNN). A lightweight parallel delta manipulator with a large workspace has been built, and a new design of a wristband in the form of a passive detachable gripper, is presented, which, under contact, automatically attaches to the human, while disengages from the manipulator. A new trajectory planning method has been used to minimize the torques caused by the external forces during contact, which cause attitude perturbations. Experiments have been done to evaluate the machine learning method for detection and location, and for the assessment of the performance of the trajectory planning method. The results show how the VGG-16 neural network provides a detection accuracy of 67.99%. Moreover, simulation experiments have been done to show that the new trajectories minimize the perturbations to the aerial platform.

This paper proposes a Cartesian control scheme applied to a robotic assistant for laparoscopic surgery. This system's main characteristic is that it emulates the movements of a human assistant, guiding the laparoscopic camera with precision to focus on the area in question inside the patient. Furthermore this control scheme requires adjustment of certain parameters in order to prevent saturation of the manipulator's actuators, and therefore the robot has been studied in terms of manipulability. The proposed movement control scheme has been implanted in the ERM robot used to carry out trials on thirty two patients

This work presents an approach to the evaluation of two interfaces for the control of a robotic surgical assistant. Each interface is associated to a different mode of controlling the system: by the surgeon (voice commands) or by the assistant (tactile interface). This two modes are allowed by the design of the manipulator, developed to occupy a small volume in the operating room. To evaluate the interfaces, a rating scale for teleoperated systems is proposed.

This paper presents an adaptive trajectory planning method concerning to the robotic assistant ERM (endoscopic robotic manipulator), designed and developed by the authors for handling the camera in laparoscopic surgery. In order to emulate the human assistant, camera movements must be defined relative to the fulcrum point, where the optic passes through the patient skin and enters inside the abdominal cavity. Since the robot has a passive wrist, and it is not fixed to the operating table, the relative position between the robot camera holder and the insertion point is unknown. In this way, the proposed approach keeps the camera orientation according to the motion references in spite of this uncertainty, and compensates other unexpected disturbances about the relative robot-patient position. This motion planner is based on a schema of a cartesian motion controller with inner joint position-velocity loop, and has been tested by means of experimentation with alive animals.

Presents a robotic assistant for helping surgeons in minimally invasive surgery. This prototype does not require any modification of a standard operation theatre (furniture or surgery tools) for its installation and its putting into operation. Due to its modular design, the robotic assistant is defined as a multi-purpose tool that has been successfully used in laparoscopic surgery, cystoscopy diagnostic and transurethral resection. The system has been tested by using both patient simulators and animals for experimentation purposes.