In this paper, we propose a dynamic model and control framework for tendon-driven continuum robots (TDCRs) with multiple segments and an arbitrary number of tendons per segment. Our approach leverages the Clarke transform, the Euler-Lagrange formalism, and the piecewise constant curvature assumption to formulate a dynamic model on a two-dimensional manifold embedded in the joint space that inherently satisfies tendon constraints. We present linear and constraint-informed controllers that operate directly on this manifold, along with practical methods for preventing negative tendon forces without compromising control fidelity. This opens up new design possibilities for overactuated TDCRs with improved force distribution and stiffness without increasing controller complexity. We validate these approaches in simulation and on a physical prototype with one segment and five tendons, demonstrating accurate dynamic behavior and robust trajectory tracking under real-time conditions.

Using compliant materials leads to continuum robots undergoing large deformations. Their nonlinear behavior motivates the use of model-based controllers. They require state estimation as an essential step to be deployed. Available sensors are usually realized by introducing rigid bodies to the soft robot or inserting soft sensors made of materials different from the robot itself. Both approaches result in changes in the system’s dynamics. Optical measurements are problematic, especially in confined spaces. This can be avoided when the sensor is located at the robot's base. This paper studies the state estimation of a pneumatically actuated soft robot using the measured forces and torques at its base. For the first time, this is done using an unscented Kalman filter without restraining the dynamics to a planar or quasi-static motion while applying it to a real system. Real-time capability is achieved with our implementation. The state estimation is tested in a Cosserat rod simulation and on the physical system. The position is estimated with an accuracy of three to five millimeters for a 130 millimeter long pneumatic robot.

Soft material robotics is a rather young research field in the robotics and material science communities. A popular design is the soft pneumatic actuator (SPA) which, if connected serially, becomes a highly compliant manipulator. This high compliance makes it possible to adapt to the environment and in the future might be very useful for manipulation tasks in narrow and wound environments. A central topic is the modelling of the manipulators. While comparatively rigid continuum robots are build of metal or other materials, that conduct a linear behaviour, the material used in soft material robotics often exhibits a nonlinear stress-strain relationship. In this paper we contribute an identification method for material parameters and data-based approach within the constitutive equations of a Cosserat rod model. We target bending and extension stiffness, consider shear and neglect torsional strains. The proposed method is applicable to any continuum robot which can be modelled by the classic theory of special Cosserat rods, including constraint models, and shows great improvement in experimental results with mean position errors of 0.59% reference length.