Soft-bodied robotic manipulators have great potential for use in minimally invasive surgery, owing to their advantages of high flexibility with infinite degrees of freedom (DOF). One of the potential applications is to perform blood suctioning, which is inevitable during the surgery. To attain higher efficiency in suctioning, the robotic tip should remain vertical while moving along on the work surface. Motivated by this application, this article presents a novel soft robot design and its control scheme to properly configure the tip of a two-segment soft robot while following a planned trajectory on the work surface. Aiming to reduce the incision size and the possibility of infection, a 3D-printed soft-bodied manipulator utilizing the cable-driven mechanism with a diameter of 9 mm was designed and fabricated. An additional DOF was added through a motorized insertion stage. The robot system was modeled using piecewise constant-curvature assumption, and an RGB-D vision was employed to enhance the accuracy of the kinematic-based controller. Performances of the tip positioning and verticalizing were evaluated via simulation, and further verified through experiments. The results confirm that the manipulator is capable of following different trajectories at various velocities while keeping its tip vertical. Compared to other similar works, our results are satisfactory with an root-mean-square error of trajectory tracking within 7 mm, and a maximum angular deviation of 6 $^\circ$ . Fluid suction experiments were conducted to demonstrate its effectiveness for automated 3-D suction. This article offers a new tool to support the surgeons for surgical blood suction.

A cable-driven soft robot with redundancy can perform the tip trajectory tracking task and in the meanwhile fulfill some extra constraints, such as tracking with a designated tip orientation, or avoiding obstacles in the environment. These constraints require proper motion planning of the soft material-based body that can be axially compressed. In this letter, we derive the compressible curvature kinematics of a cable-driven soft robot which takes the undesirable axial compression caused by the cable-driven mechanism into account. Robot motion planning for tip trajectory tracking tasks in constrained conditions, including fixed orientation tip and manipulator–obstacle collision avoidance, are investigated. The inverse solution of cable actuation is formulated as a damped least-square optimization problem and iteratively computed off-line. The performance of path and trajectory tracking, and the obedience to constraints are evaluated via the simulation we make open-source, as well as prototype experiments. The method can be generalized to similar multisegment cable-driven soft robotic systems by customizing the robot parameters for the prior motion planning in tip trajectory following tasks.

Finding the shape of a continuum robot is a challenging task, especially in a constrained environment where external sensors like cameras are unable to provide sufficient information. In particular, accurate robot control becomes more difficult when the robot needs to interact with uncertain external payloads. In this article, we present the development of a soft robotic system with embedded sensors to help reconstruct the shape of the robot under different external disturbances. First, strain gauges were employed to perceive the current deformation state of the robot due to actuator inputs and external payloads. Then, a shape reconstruction (SR) method based on a spatial curve fitting approach was proposed, where multiple control points along the robot were predicted using Neural Networks. With the estimated shape, a local inverse kinematics model was developed so that the robot end-effector can be precisely controlled in quasi-static state to reach various positions, and position of end effector calculated via SR module was employed to improve the path following performance. Simulation and experiments were conducted and the results confirm that the proposed control system is effective to predict the shape and properly control the robot with or without external payloads.

A soft-bodied robot exhibits prominent dexterity due to the soft nature of its material. However, the softness can become a burden when the robot needs to interact with the environment, given that the targeted object is usually much stiffer than the compliant soft robot. A variable-stiffness soft robot, fusing the merits of softness and stiffness, is in favor of many applications, such as robot-assisted minimally invasive surgeries. In this article, we propose a tendon-tensioning method to adaptively control the stiffness of a dual-segment tendon-driven backboneless soft robot based on depth vision. A depth-vision-based closed-loop controller is designed for stiffness compensation when the manipulator is subjected to the external load. Experiments were conducted to examine the feasibility and performance of the proposed method. The results confirm our control scheme on the robot with controllability of stiffness up to 132%. Based on our method, the manipulator with an external payload can follow designated trajectories with positioning errors reduced up to 50% comparing to that with open-loop control. Without quantifying the instantaneous stiffness, this work contributes a generalized method for tuning the stiffness of the tendon-driven soft robots in the presence of external disturbances without onboard sensing.

Cell manipulation is imperative to the areas of cellular biology and tissue engineering, providing them a useful tool for patterning cells into cellular patterns for different analyses and applications. This paper presents a novel approach to perform three-dimensional (3D) cell manipulation and patterning with a multi-layer engineered scaffold. This scaffold structure employed dielectrophoresis as the non-contact mechanism to manipulate cells in the 3D domain. Through establishing electric fields via this multi-layer structure, the cells in the medium became polarized and were attracted towards the interior part of the structure, forming 3D cellular patterns. Experiments were conducted to evaluate the manipulation and the patterning processes with the proposed structure. Results show that with the presence of a voltage input, this multi-layer structure was capable of manipulating different types of biological cells examined through dielectrophoresis, enabling automatic cell patterning in the time-scale of minutes. The effects of the voltage input on the resultant cellular pattern were examined and discussed. Viability test was performed after the patterning operation and the results confirmed that majority of the cells remained viable. After 7 days of culture, 3D cellular patterns were observed through SEM. The results suggest that this scaffold and its automated dielectrophoresis-based patterning mechanism can be used to construct artificial tissues for various tissue engineering applications.

Robot-assisted surgery has revolutionized the field of surgery over the past few decades. Despite many successes, achieving full automation in these surgeries remains a challenging task. In this paper, a dynamic approach is proposed to automate knot tying with an in-house robot vision system. Through efficient path planning and coordination between two grippers, the workspace required for constructing the suture loop can be reduced while issues such as suture slippage and collisions between instruments can be eliminated. Visual images were employed to monitor the two grippers in real time and their positions were evaluated using transformation matrices obtained experimentally. A linear quadratic control scheme was applied to optimize the tracking performance of the two grippers. From the experiments, this visual evaluation method can achieve a position accuracy of 1 mm in the workspace. The proposed algorithm was evaluated and automatic suture looping operation was successfully performed in all six trials. Different parameters in the control scheme were also examined by introducing external impulse disturbances during the knot-tying process. This proposed knot-tying approach demonstrates a simple and efficient way to construct a suture knot in a minimal workspace.