Continuum manipulators which are robot limbs inspired by trunks, snakes, and tentacles, represent a promising field in robotic manipulation research. They are well known for their compliance, as they can conform to the shape of objects they interact with. Furthermore, they also benefit from improved dexterity and reduced weight compared to traditional rigid manipulators. The current state of the art continuum robots typically consists of a bulky pneumatic or tendon-driven actuation system at the base, hindering their scalability. Additionally, they tend to sag due to their own weight and are weak in the torsional direction, limiting their performance under external load. This work presents an origami-inspired cable-driven continuum manipulator module that offers low-cost, light-weight, and is inherently safe for human-robot interaction. This dissertation includes contributions in the design of the modular and torsionally strong continuum robot, the motion planning and control of the system, and finally the embedded sensing to close the loop providing robust feedback.

Continuum manipulators which are robot limbs inspired by trunks, snakes, and tentacles, represent a promising field in robotic manipulation research. They are well known for their compliance, as they can conform to the shape of objects they interact with. Furthermore, they also benefit from improved dexterity and reduced weight compared to traditional rigid manipulators. The current state of the art continuum robots typically consists of a bulky pneumatic or tendon-driven actuation system at the base, hindering their scalability. Additionally, they tend to sag due to their own weight and are weak in the torsional direction, limiting their performance under external load. This work presents an origami-inspired cable-driven continuum manipulator module that offers low-cost, light-weight, and is inherently safe for human-robot interaction. This dissertation includes contributions in the design of the modular and torsionally strong continuum robot, the motion planning and control of the system, and finally the embedded sensing to close the loop providing robust feedback.