A variable-stiffness continuum manipulators by an SMA-based sheath in minimally invasive surgery

Variable stiffness performance analysis of layer jamming actuator based on bionic adhesive flaps

Soft actuators made of soft materials cannot generate precisely efficient output forces compared to rigid actuators. It is a promising strategy to equip soft actuators with variable stiffness modules of layer jamming mechanism, which could increase their stiffness as needed. Inspired by the gecko's the array of setae, bionic adhesive flaps with inclined micropillars are applied in layer jamming mechanism. In this paper, after the manufacturing process of the layer jamming actuator based on the bionic adhesive flaps is described, the equivalent stiffness models of the whole actuator are established in the unjammed and jammed states. And the shear adhesive force of a single micropillar is calculated based on the Kendall viscoelastic band model. The finite element simulation results of two bionic adhesive flaps show that the interlaminar shear stress and stiffness increase with the increase of pressure. The measurement of shear adhesive force show that the critical shear adhesive force of the bionic adhesive material is 3.2 times that of polyethylene terephthalate (PET) material, and exhibit the ability of anisotropic adhesion behavior. The variable stiffness performance of the layer jamming actuator based on bionic adhesive flaps is evaluated by three test methods, and the max stiffness reaches 8.027 N mm-1, which is 1.5 times higher than the stiffness of the layer jamming actuator based on the PET flaps. All results of simulation and experiment effectively verify the validity and superiority of applying the bionic adhesive flaps to the layer jamming mechanism to enhance the stiffness.

Design and simulation verification of clamping instrument with active variable stiffness for pelvic fracture reduction

BACKGROUND

During the robot-assisted pelvic fracture reduction process, the clamping instrument are subjected to the large reduction force from the robot, resulting in inevitable great stress concentration and deformation of the bone pins, affecting the fracture reduction accuracy.

METHOD

A compact and easily-to-adjust clamping instrument with active variable stiffness is designed. The relationship between the component's elongation and the clamping instrument's deformation and stiffness is derived and calculated. Furthermore, the finite element model of the fixed and the variable stiffness clamping instruments connecting with the injured pelvic musculoskeletal tissue is developed, respectively.

RESULTS

Applying the same reduction force, the deformation of the clamping instrument with variable stiffness is reduced, especially in the elongated state. Moreover, the new clamping instrument meets the strength requirements and makes a better stress distribution.

CONCLUSION

The clamping instrument can achieve stiffness adjustment during the reduction process and will be used for improving the surgery accuracy.

Static Modeling of a Class of Stiffness-Adjustable Snake-Like Robots with Gravity Compensation

Stiffness-adjustable snake-like robots have been proposed for various applications, including minimally invasive surgery. Based on a variable neutral-line mechanism, previous works proposed a class of snake-like robots that can adjust their stiffness by changing the driving cables’ tensions. A constant curvature hypothesis was used to formulate such robots’ kinematics and was further verified by our previous work via rigorous force analysis and ADAMS simulations. However, all these models and analyses have ignored the effect of the robot links’ gravity, resulting in significant errors in real systems. In this paper, a static model considering gravity compensation is proposed for the stiffness-adjustable snake-like robots. The proposed model adopts a nonlinear Gauss–Seidel iteration scheme and consists of two parts: gravity update and pose estimation. In each iteration, the former updates the payload of each link caused by gravity, and the latter estimates the pose of the robot by refreshing the angle and position values. This iteration stops when the change in the tip position is less than a pre-set error ϵ. During the above process, the only dependent information is each cable’s tension. Simulations and experiments are carried out to verify the effectiveness of the proposed model. The impact of gravity is found to increase with growing material densities in the simulations. The experimental results further indicate that compared with a model without gravity compensation, our model reduces the tip estimation error by 91.5% on average.

QPSO-MPC based tracking algorithm for cable-driven continuum robots

Cable-driven continuum robots (CDCRs) can flexibly travel through narrow space for complex workspace tasks. However, it is challenging to design the trajectory tracking algorithm for CDCRs due to their nonlinear dynamic behaviors and cable hysteresis characteristics. In this contribution, a model predictive control (MPC) tracking algorithm based on quantum particle swarm optimization (QPSO) is designed for CDCRs to realize effective trajectory tracking under constraints. In order to make kinematic analysis of a CDCR, the forward and inverse mapping among actuation space, joint space and work space is analyzed by using the piecewise constant curvature method and the homogeneous coordinate transformation. To improve the performance of conventional MPC for complex tracking tasks, QPSO is adopted in the rolling optimization of MPC for its global optimization performance, robustness and fast convergence. Both simulation and operational experiment results demonstrate that the designed QPSO-MPC presents high control stability and trajectory tracking precision. Compared with MPC and particle swarm optimization (PSO) based MPC, the tracking error of QPSO-MPC is reduced by at least 43 and 24%, respectively.

A Survey on Design, Actuation, Modeling, and Control of Continuum Robot

In this paper, we describe the advances in the design, actuation, modeling, and control field of continuum robots. After decades of pioneering research, many innovative structural design and actuation methods have arisen. Untethered magnetic robots are a good example; its external actuation characteristic allows for miniaturization, and they have gotten a lot of interest from academics. Furthermore, continuum robots with proprioceptive abilities are also studied. In modeling, modeling approaches based on continuum mechanics and geometric shaping hypothesis have made significant progress after years of research. Geometric exact continuum mechanics yields apparent computing efficiency via discrete modeling when combined with numerical analytic methods such that many effective model-based control methods have been realized. In the control, closed-loop and hybrid control methods offer great accuracy and resilience of motion control when combined with sensor feedback information. On the other hand, the advancement of machine learning has made modeling and control of continuum robots easier. The data-driven modeling technique simplifies modeling and improves anti-interference and generalization abilities. This paper discusses the current development and challenges of continuum robots in the above fields and provides prospects for the future.