Controlling stiffness is critical in procedures using soft surgical robots. In the final year of the STIFF-FLOP project, the University of Surrey developed a methodology to characterise the tuneable dynamic stiffness matrix and demonstrated its use for rejecting lateral and normal disturbances. This method of disturbance rejection was employed in conjunction with granular jamming to maintain the tip position of a three-segment STIFF-FLOP robot.
It is noted that this algorithm can be extended to multi-module soft robots. The research conducted by UoS verified why the reduction of stiffness at the tip is preferred for safety whilst greater stiffness is essential to undertake efficient tissue manipulation with surgical tools.
Furthermore, information on the forces exerted at the distal end of the robot manipulator and appropriate feedback control improved the robustness of motion of the system and contributed to the improvement of robot-environment interaction safety through precise manipulation.
An overview of the STIFF-FLOP robot integrated with the industrial MELFA RV-1A robot and a suite of force sensors for performing cutting and ablation is shown on the left side.
Furthermore, UoS has developed an innovative 2D-soft phantom organ test bed representing the abdominal cavity and its organs, which has been instrumented with UoS-proprietary 3d-force sensor grids (monitoring pressure and in-plane stresses at all grid nodes). The test bed was used to monitor pressure and friction forces on the bowel and uterus sides as the three-segment STIFF-FLOP arm moved and was actuated in the channel between the bowel and the uterus, and to successfully verify that the STIFF-FLOP arm caused no damage to the soft organs and grid sensors, for forces up to 20N when the hard connections between modules were manually pressed and moved tangentially across the surface of the soft organs.