Highly stretchable-compressible coiled polymer sensor for soft continuum manipulator

In recent years, soft continuum robots have become emerging research hotspots, but sensing of the robot shape needs to be addressed for precise control. To solve this problem, we present an optical coiled polymer sensor that can measure strain based on macro bending power loss. Proposed sensor is fabricated by coiling and annealing a polymer optical fiber of diameter 0.25 mm. Under applied strain, the bending curvature of the coiled sensor changes which leads to light intensity change. Due to its coiled structure, the proposed sensor can measure both tensile and compressive strain in a wide range (> 250 %). Static and dynamic responses of the proposed sensor were observed by controlling the design parameters, such as spring diameter and number of coils. Fabricated coiled polymer sensor with a light-weight (< 0.5 g) and compact structure showed a high stretchability-compressibility, high stability, and low hysteresis error. By placing three fabricated sensors inside the soft continuum manipulator, a 3-degree-of-freedom (DOF) configuration including bending and torsion motions can be obtained. We used an artificial neural network to derive the relationship between the sensor outputs and the 3 DOFs configuration of the soft continuum manipulator. The results showed that the configuration of the soft continuum manipulator can be obtained in real-time with high accuracy (error < 2.17 %).

Development of a Modular Tensegrity Robot Arm Capable of Continuous Bending

In this study, we present a tensegrity robot arm that can reproduce the features of complex musculoskeletal structures, and can bend like a continuum manipulator. In particular, we propose a design method for an arm-type tensegrity robot that has a long shape in one direction, and can be deformed like a continuum manipulator. This method is based on the idea of utilizing simple and flexible strict tensegrity modules, and connecting them recursively so that they remain strict tensegrity even after being connected. The tensegrity obtained by this method strongly resists compressive forces in the longitudinal direction, but is flexible in the bending direction. Therefore, the changes in stiffness owing to internal forces, such as in musculoskeletal robots, appear more in the bending direction. First, this study describes this design method, then describes a developed pneumatically driven tensegrity robot arm with 20 actuators. Next, the range of motion and stiffness under various driving patterns are presented as evaluations of the robot performance.

A learning-based tip contact force estimation method for tendon-driven continuum manipulator

Although tendon-driven continuum manipulators have been extensively researched, how to realize tip contact force sensing in a more general and efficient way without increasing the diameter is still a challenge. Rather than use a complex modeling approach, this paper proposes a general tip contact force-sensing method based on a recurrent neural network that takes the tendons’ position and tension as the input of a recurrent neural network and the tip contact force of the continuum manipulator as the output and fits this static model by means of machine learning so that it may be used as a real-time contact force estimator. We also designed and built a corresponding three-degree-of-freedom contact force data acquisition platform based on the structure of a continuum manipulator designed in our previous studies. After obtaining training data, we built and compared the performances of a multi-layer perceptron-based contact force estimator as a baseline and three typical recurrent neural network-based contact force estimators through TensorFlow framework to verify the feasibility of this method. We also proposed a manually decoupled sub-estimators algorithm and evaluated the advantages and disadvantages of those two methods.

Dynamic Modeling and Experimental Verification of A Cable-Driven Continuum Manipulator With Cable-Constrained Synchronous Rotating Mechanisms

The cable-driven segmented manipulator with cable-constrained synchronous rotating mechanisms (CCSRM) is a new type of continuum manipulator, which has large stiffness and less motors, and thus exhibits excellent comprehensive performance. This paper presents a dynamic modeling method for this type of manipulator to analyze the friction and deformation of the cables on the dynamical behaviors of the system. First, the driving cables are modeled based on the ALE formulation, the strategies for detecting stick-slip transitions are proposed by using a trial-and-error algorithm, and the stiff problems of the dynamic equations are released by a model smoothing method. Second, the dynamic modeling method for rigid links is presented by using quaternion parameters. Third, the connecting cables are modeled by torsional spring-dampers and the frictions between the connecting cables and the conduits are considered based on a modified Coulomb friction model. Finally, the numerical results are presented and verified by comparing with experiment results. The study shows that the friction and cable deformation play an important role in the dynamical behaviors of the manipulator. Due to these two factors, the constant curvature bending of the segments does not remain.