Method for Robot Manipulator Joint Wear Reduction by Finding the Optimal Robot Placement in a Robotic Cell

We describe a method for robotic cell optimization by changing the placement of the robot manipulator within the cell in applications with a fixed end-point trajectory. The goal is to reduce the overall robot joint wear and to prevent uneven joint wear when one or several joints are stressed more than the other joints. Joint wear is approximated by calculating the integral of the mechanical work of each joint during the whole trajectory, which depends on the joint angular velocity and torque. The method relies on using a dynamic simulation for the evaluation of the torques and velocities in robot joints for individual robot positions. Verification of the method was performed using CoppeliaSim and a laboratory robotic cell with the collaborative robot UR3. The results confirmed that, with proper robot base placement, the overall wear of the joints of a robotic arm could be reduced from 22% to 53% depending on the trajectory.

Robot-assisted laparoscopic antegrade versus open inguinal lymphadenectomy: a retrospective controlled study

Background To investigate the surgical methods and clinical results of robot-assisted laparoscopic antegrade inguinal lymphadenectomy. Methods A retrospective study was performed on clinical data from 19 patients with penile cancer admitted from March 2013 to October 2017. Among them, nine patients underwent robot-assisted laparoscopic antegrade inguinal lymphadenectomy (robot-assisted group) and 10 patients underwent open inguinal lymphadenectomy (open group). In the robot-assisted group, preoperative preparation, patient position, robot placement, design of operating channel and establishment of operating space are described. Key surgical procedures and techniques are also summarized. In addition, the number of lymph nodes removed, postoperative complications and follow-up in both groups were statistically analyzed. Results For the 9 patients in the robot-assisted group, surgery was successfully accomplished at 17 sides without intraoperative conversion to open surgery. The surgery time for each side was 45~90 min using laparoscope with an average of 68.5 ± 13.69 min/side. The intraoperative blood loss was estimated to be < 10 ml/side, and the number of removed lymph nodes was not significantly different from that of the open group (12 ± 4.2/side vs.11 ± 5.8/side, P = 0.84). There were no postoperative complications such as skin necrosis, delayed wound healing and cellulitis in the robot-assisted group. Skin-related complications occurred in 9 (45%) of the 20 sides in the open group. During a median follow-up of 25 months in robot-assisted group and 52.5 mouths in open group, was not significantly different there were no statistical differences in recurrence-free survival between the groups (75% vs 60%, p = 0.536). Conclusion Robot-assisted laparoscopic antegrade inguinal lymphadenectomy achieved the desired surgical outcomes with fewer intraoperative and postoperative complications. The robotic arms of the surgical system were placed between the lower limbs of each patient. There was no need to re-position the robotic arms during bilateral inguinal lymphadenectomy. This simplified the procedure and reduced the use of trocars. If necessary, pelvic lymphadenectomy could be performed simultaneously using the original trocar position.

Determining Feasible Robot Placements in Robotic Cells for Composite Prepreg Sheet Layup

High-performance composites are widely used in industry because of specific mechanical properties and lightweighting opportunities. Current automation solutions to manufacturing components from prepreg (pre-impregnated precursor material) sheets are limited. Our previous work has demonstrated the technical feasibility of a robotic cell to automate the sheet layup process. Many decisions are required for the cell to function correctly, and the time necessary to make these decisions must be reduced to utilize the cell effectively. Robot placement with respect to the mold is a significant and complex decision problem. Ensuring that robots can collaborate effectively requires addressing multiple constraints related to the robot workspace, singularity, and velocities. Solving this problem requires developing computationally efficient algorithms to find feasible robot placements in the cell. We describe an approach based on successive solution refinement strategy to identify a cell design that satisfies all constraints related to robot placement.