Soft actuators made of highly elastic polymers allow novel robotic system designs, yet application-specific soft robotic systems are rarely reported. Taking notice of the characteristics of soft pneumatic actuators (SPAs) such as high customizability and low inherent stiffness, we report in this work the use of soft pneumatic actuators for a biomedical use - the development of a soft robot for rodents, aimed to provide a physical assistance during gait rehabilitation of a spinalized animal. The design requirements to perform this unconventional task are introduced. Customized soft actuators, soft joints and soft couplings for the robot are presented. Live animal experiment was performed to evaluate and show the potential of SPAs for their use in the current and future biomedical applications.

The number of ropes for a fully constrained, tendon-based robot has to be larger than the actuated degrees of freedom since ropes only impose unidirectional constraints. This actuation redundancy implicates that more position information is available than would be required for the the determination of the end-effector pose. This leads to an optimization problem for the forward kinematics of the robot which has to be solved in real-time. Furthermore, the kinematics of tendon-based robots are often kept simple in existing systems by guiding the ropes through holes into the workspace. This facilitates the description of the rope vectors. However, this solution is not applicable for high-load applications, as friction would cause excessive non-linearities and wear. To solve the forward kinematics of tenon-based robots, we introduce a physics-based interpretation of the mentioned optimization problem. The robotic system is described as a damped oscillator whose resting position is equal to the optimal solution. As a major advantage over the known algorithms, this physics-based approach is quantifiable in terms of accuracy of the solution and number of iterations. Furthermore, the design and mathematical description of a deflection unit's geometry is presented. This deflection unit guides the rope smoothly into the workspace and its relevant influence on the kinematic equations can be compensated. The physics-based approach is experimentally evaluated on a tendon-based haptic interface, the r3-system, and it is compared to the solutions using only the minimum set of sensor information.

This paper presents the design of a new user-cooperative rope robot. This robot serves as a large-scale haptic interface in a multi-modal Cave environment used for sport simulation. In contrast to current rope robots, the configuration of the presented robot is adaptable to different simulation tasks what makes the robot more versatile. However, this adaptability and the high dynamics in sports lead to challenging requirements and specific design criteria of the hardware components. We present the requirements on the single robot components as well as the design of the entire setup optimized in terms of user-cooperativity and versatility. The setup includes sensors to measure the relevant parameters for user-cooperative control, i.e. position with a high resolution and the rope forces. Furthermore, an algorithm is introduced, which calculates the distance between the single ropes and the user in order to avoid collisions between the ropes and the user. Single points on the user's body are, therefore, tracked with a motion tracking system; the user's single body parts are then represented by geometrical objects whose distances to the ropes are calculated. The algorithm is programmed in such way that the collision detection runs in real-time. Both, the hardware and the algorithm, were evaluated experimentally in two applications, a rowing simulator and a tennis application. The hardware concept combined with the distance calculation allows the use of new kinematic concepts and expands the spectrum of realizable movement tasks that can be implemented into the Cave environment.

The rehabilitation robot LOKOMAT has been developed at University Hospital Balgrist to automate treadmill training of spinal cord injury and stroke patients. Current rehabilitation training on that robot consists of moving the patient's legs on predefined trajectories. However, this kind of training is not challenging, as patients are moved regardless of their efforts and do not see their advancement. To enhance rehabilitation training with the LOKOMAT, a virtual reality setup was installed. It consists of a passive stereo projection system (screen size 3 m times 2 m), a Dolby 5.1 sound system and an electric fan. With that setup an obstacle crossing scenario was implemented. The patients can see their advancement on the screen, as an animated figurine (avatar) moves along a path simultaneously with their own movements. Additionally they can hear sounds (e.g. environmental sounds, steps), feel the wind, and experience force feedback, provided by the orthosis, when hitting obstacles. The objective of a first study on visual feedback was to investigate which feedback suits best to perceive the obstacle distances and heights correctly. To answer this question, 14 healthy subjects walked in the actuated gait orthosis, received visual feedback and tried to avoid collisions with obstacles. Subjects could move freely within the gait orthosis and determine their own speed and step length. They had to cross the obstacles independently, with haptic feedback, indicating obstacle hits. Results show that the side view results in least obstacle hits and that 2D excels 3D display in this respect