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  1. Tendon actuated multisection continuum arms have high potential for inspection applications in highly constrained spaces. They generate motion by axial and bending deformations. However, because of the high mechanical coupling between continuum sections, variable length-based kinematic models produce poor results. A new mechanics model for tendon actuated multisection continuum arms is proposed in this paper. The model combines the continuum arm curve parameter kinematics and concentric tube kinematics to correctly account for the large axial and bending deformations observed in the robot. Also, the model is computationally efficient and utilizes tendon tensions as the joint space variables thus eliminating the actuator length related problems such as slack and backlash. A recursive generalization of the model is also presented. Despite the high coupling between continuum sections, numerical results show that the model can be used for generating correct forward and inverse kinematic results. The model is then tested on a thin and long multisection continuum arm. The results show that the model can be used to successfully model the deformation. 
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  2. In this paper, we propose and investigate a new approach to modeling variable curvature continuum robot sections, based on Euler spirals. Euler spirals, also termed Clothoids, or Cornu spirals, are those curves in which the curvature increases linearly with their arc length. In this work, Euler spirals are applied to the kinematic modeling of continuum robots for the first time. The approach was evaluated using the sections of numerous continuum robots, including two novel parallel continuum robots. Each robot consists of three parallel sections, each with three thin, long McKibben actuators. These sections are poorly modeled by the widely used constant curvature kinematic model. The constant curvature and Euler spiral models were compared and the Euler spiral method was seen to be a significantly better match for a wide range of configurations of the robot hardware. 
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