A Multi-Sensorial Hybrid Control for Robotic Manipulation in Human-Robot Workspaces

Autonomous manipulation in semi-structured environments where human operators can interact is an increasingly common task in robotic applications. This paper describes an intelligent multi-sensorial approach that solves this issue by providing a multi-robotic platform with a high degree of autonomy and the capability to perform complex tasks. The proposed sensorial system is composed of a hybrid visual servo control to efficiently guide the robot towards the object to be manipulated, an inertial motion capture system and an indoor localization system to avoid possible collisions between human operators and robots working in the same workspace, and a tactile sensor algorithm to correctly manipulate the object. The proposed controller employs the whole multi-sensorial system and combines the measurements of each one of the used sensors during two different phases considered in the robot task: a first phase where the robot approaches the object to be grasped, and a second phase of manipulation of the object. In both phases, the unexpected presence of humans is taken into account. This paper also presents the successful results obtained in several experimental setups which verify the validity of the proposed approach

Design of a robotic transcranial magnetic stimulation system

Transcranial Magnetic Stimulation (TMS) is an excellent and non-invasive technique for studying the human brain. Accurate placement of the magnetic coil is required by this technique in order to induce a specific cortical activity. Currently, the coil is manually held in most of stimulation procedures, which does not achieve the precise clinical evaluation of the procedure. This thesis proposes a robotic TMS system to resolve these problems as a robot has excellent locating and holding capabilities. The proposed system can track in real-time the subject’s head position and simultaneously maintain a constant contact force between the coil and the subject’s head so that it does not need to be restrained and thus ensure the accuracy of the stimulation result. Requirements for the robotic TMS system are proposed initially base on analysis of a serial of TMS experiments on real subjects. Both hardware and software design are addressed according to these requirements in this thesis. An optical tracking system is used in the system for guiding and tracking the motion of the robot and inadvertent small movements of the subject’s head. Two methods of coordinate system registration are developed base on DH and Tsai-lenz’s method, and it is found that DH method has an improved accuracy (RMS error is 0.55mm). In addition, the contact force is controlled using a Force/Torque sensor; and a combined position and force tracking controller is applied in the system. This combined controller incorporates the position tracking and conventional gain scheduling force control algorithms to monitor both position and force in real-time. These algorithms are verified through a series of experiments. And it is found that the maximum position and force error are 3mm and 5N respectively when the subject moves at a speed of 20mm/s. Although the performance still needs to be improved to achieve a better system, the robotic system has shown the significant advantage compared with the manual TMS system. Keywords—Transcranial Magnetic Stimulation, Robot arm, Medical system, Calibration, TrackingEThOS - Electronic Theses Online ServiceGBUnited Kingdo

Design of a robotic transcranial magnetic stimulation system

Transcranial Magnetic Stimulation (TMS) is an excellent and non-invasive technique for studying the human brain. Accurate placement of the magnetic coil is required by this technique in order to induce a specific cortical activity. Currently, the coil is manually held in most of stimulation procedures, which does not achieve the precise clinical evaluation of the procedure. This thesis proposes a robotic TMS system to resolve these problems as a robot has excellent locating and holding capabilities. The proposed system can track in real-time the subject’s head position and simultaneously maintain a constant contact force between the coil and the subject’s head so that it does not need to be restrained and thus ensure the accuracy of the stimulation result. Requirements for the robotic TMS system are proposed initially base on analysis of a serial of TMS experiments on real subjects. Both hardware and software design are addressed according to these requirements in this thesis. An optical tracking system is used in the system for guiding and tracking the motion of the robot and inadvertent small movements of the subject’s head. Two methods of coordinate system registration are developed base on DH and Tsai-lenz’s method, and it is found that DH method has an improved accuracy (RMS error is 0.55mm). In addition, the contact force is controlled using a Force/Torque sensor; and a combined position and force tracking controller is applied in the system. This combined controller incorporates the position tracking and conventional gain scheduling force control algorithms to monitor both position and force in real-time. These algorithms are verified through a series of experiments. And it is found that the maximum position and force error are 3mm and 5N respectively when the subject moves at a speed of 20mm/s. Although the performance still needs to be improved to achieve a better system, the robotic system has shown the significant advantage compared with the manual TMS system. Keywords—Transcranial Magnetic Stimulation, Robot arm, Medical system, Calibration, TrackingEThOS - Electronic Theses Online ServiceGBUnited Kingdo