This paper presents a detailed user study aimed at experimentally comparing the experience levels within bi-lateral teleoperation. The primary objective is to elucidate the key performance metrics that can effectively evaluate the competency level of human operators. Existing methodologies typically focus on the quantitative psychological evaluation of human-in-the-loop systems rather than operator performance. In our experimental study, six novice and four professional operators participated in various telerobotic activities. Various parameters, including task completion duration, errors, remote manipulators' motion, and subjects' gaze information, were captured. Subsequently, the measured performance parameters across all subjects were compared with respect to their level of proficiency through statistical analyses. The results indicate that tasks were performed more quickly by experienced operators, fewer mistakes were made, and remote manipulators were operated more smoothly (e.g., fewer jerks and better maintenance within the centre of the workspace). Additionally, better compensation for the lack of depth perception was demonstrated by experienced operators through effective scanning of multiple viewpoints.

Unmanned underwater vehicles are crucial for deep-sea exploration and inspection without imposing any danger to human life due to extreme environmental conditions. But, designing a robust controller that can cope with model uncertainties, external disturbances, and time delays for such vehicles is a challenge. This paper implements a sliding mode position control algorithm with a time-delay estimation term to a remotely operated underwater vehicle to deal with disturbances, such as waves, and time delays. The controller is implemented on an underwater vehicle (BlueRov) and compared with a proportional-integral-derivative (PID) controller in a wave tank with different disturbances and when there exist delays within the communication channel. The experimental results show that the proposed control method provides better performance than the conventional PID in the presence of extreme disturbances with less control efforts.

Assessment of minimally invasive surgical skills is a non-trivial task, usually requiring the presence and time of expert observers, including subjectivity and requiring special and expensive equipment and software. This study develops an algorithm for tracking laparoscopy instruments in the video cues of a standard laparoscopy training box with a single webcam camera and proposes new criteria to assess skill level using the extracted tool trajectories. Instrument tracking and assessment criteria together constitute a significant step towards developing a low cost, automated, and widely applicable laparoscopy training and assessment system using a standard physical training box equipped with a webcam. The developed visual tracking algorithm recovers the 3D positions of the laparoscopic instruments tips to which simple colored tapes (markers) are attached. The new assessment criteria are based on frequency analysis and linear discriminant analysis of the 3D reconstructed trajectories of the instruments. The performance of these proposed criteria are compared to the conventional criteria for laparoscopy training and demonstrated to be superior on the data we have recorded from six professional laparoscopy surgeons and ten novice subjects.

This paper presents measurements of human hand-impedance during a laparoscopic training program with physically interactive robotic manipulators. The knowledge of how the hand-impedance changes due to training might be useful to inform better training programs and to introduce co-manipulated robotic assistants for effective trainings. Ten novice subjects participated in a three weeks training program for a suturing activity in laparoscopy. The subjects have been instructed to set the needle, enter the skin, and tie knots by using laparoscopic tools within a Minimally Invasive Surgery training box. Variable admittance controlled robots, attached to the tools with force sensors, applied step vice velocity disturbances while subjects were trying to set the needle. Based on the interaction force and end-effector position information, impedances of the left and right hands were computed in four different directions. The computed results were compared with respect to the participants skill progression.