Joachim von Zitzewitz

A versatile wire robot concept as a haptic interface for sport simulation

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 users body are, therefore, tracked with a motion tracking system; the users 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.

Soft robot for gait rehabilitation of spinalized rodents

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.

A tendon-based parallel robot applied to motor learning in sports

Research in multimodal motor learning in sports is highly demanding with respect to the equipment, especially when the same equipment has to be reconfigured for different applications. In our multimodal motion synthesis lab (M3-lab) we apply visual, auditory, and haptic displays as well as feedback to enhance human motor learning. The demands on our haptic display, a tendon-based parallel robot (TBPR), are particularly high: a large workspace needs to be covered, the robotic device must be versatile, the visual and auditory modality should not be affected, high velocities and forces have to be realizable to render different sports applications, and user-cooperative control strategies should be applicable.

Forward kinematics of redundantly actuated, tendon-based robots

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 units 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.

Patient-Driven Cooperative Gait Training with the Rehabilitation Robot Lokomat

Rehabilitation robots can support the training of patients with neurological gait disorders. Classical control approaches permit patients to remain passive during the robot-assisted training. We hypothesize that promoting active participation of patients will improve training efficacy. In this paper, we evaluate the combination of two existing patient-cooperative control strategies. These strategies are applicable to robotic exoskeletons that assist a patient walking on a treadmill. The first strategy, Automatic treadmill speed adaptation, detects the patient’s desired walking speed and accelerates the treadmill accordingly. The second strategy, Path control, provides spatial guidance of the legs via the rehabilitation robot while the patient controls the timing of his/her movements. We demonstrate that both strategies can be successfully combined towards an approach that allows subjects to walk on their own with the support of a robot instead of being passively moved.

Quantifying the Human Likeness of a Humanoid Robot

In research of human-robot interactions, human likeness (HL) of robots is frequently used as an individual, vague parameter to describe how a robot is perceived by a human. However, such a simplification of HL is often not sufficient given the complexity and multidimensionality of human-robot interaction. Therefore, HL must be seen as a variable influenced by a network of parameter fields. The first goal of this paper is to introduce such a network which systematically characterizes all relevant aspects of HL. The network is subdivided into ten parameter fields, five describing static aspects of appearance and five describing dynamic aspects of behavior. The second goal of this paper is to propose a methodology to quantify the impact of single or multiple parameters out of these fields on perceived HL. Prior to quantification, the minimal perceivable difference, i.e. the threshold of perception, is determined for the parameters of interest in a first experiment. Thereafter, these parameters are modified in whole-number multiple of the threshold of perception to investigate their influence on perceived HL in a second experiment. This methodology was illustrated on the parameters speed and sequencing (onset of joint movements) of the parameter field movement as well as on the parameter sound. Results revealed that the perceived HL is more sensitive to changes in sequencing than to changes in speed. The sound of the motors during the movement also reduced perceived HL. The presented methodology should guide further, systematic explorations of the proposed network of HL parameters in order to determine and optimize acceptance of humanoid robots.

Voluntary gait speed adaptation for robot-assisted treadmill training

Robot-assisted gait training currently lacks the possibility of the robot to automatically adapt to the patients needs and demands (so called “bio-cooperative control strategies”). It is desired to give the patient voluntary control over training parameters such as gait speed or joint trajectories. We implemented a control algorithm for the driven gait orthosis Lokomat that allows severely disabled stroke patients a limited and safe allowance of influence on their gait speed. To exercise gait symmetry, our algorithm can be configured such that only activity in the paretic leg will cause changes in treadmill speed. The algorithm was successfully tested with eight healthy subjects and six stroke patients.

A reconfigurable, tendon-based haptic interface for research into human-environment interactions

Human reaction to external stimuli can be investigated in a comprehensive way by using a versatile virtual-reality setup involving multiple display technologies. It is apparent that versatility remains a main challenge when human reactions are examined through the use of haptic interfaces as the interfaces must be able to cope with the entire range of diverse movements and forces/torques a human subject produces. To address the versatility challenge, we have developed a large-scale reconfigurable tendon-based haptic interface which can be adapted to a large variety of task dynamics and is integrated into a Cave Automatic Virtual Environment (CAVE). To prove the versatility of the haptic interface, two tasks, incorporating once the force and once the velocity extrema of a human subjects extremities, were implemented: a simulator with 3-DOF highly dynamic force feedback and a 3-DOF setup optimized to perform dynamic movements. In addition, a 6-DOF platform capable of lifting a human subject off the ground was realized. For these three applications, a position controller was implemented, adapted to each task, and tested. In the controller tests with highly different, task-specific trajectories, the three robot configurations fulfilled the demands on the application-specific accuracy which illustrates and confirms the versatility of the developed haptic interface.

A multidirectional gravity-assist algorithm that enhances locomotor control in patients with stroke or spinal cord injury

A robotic harness optimizing gravity-dependent gait interactions enables natural locomotion across activities of daily living in people with spinal cord injury or stroke. Greater gait with gravity Often taken for granted, gravity—the force that keeps you on the ground—becomes a notable challenge during rehabilitation from injury. Mignardot et al. “harnessed” gravity to test whether upward and forward forces, applied to the torso via a robotic body weight supportive device, assist with locomotion. Patients recovering from stroke or spinal cord injury demonstrated improved gait performance with the robotic harness. An important component of the gravity-assistive approach is an algorithm that adjusts the forces provided by the robotic harness according to the patient’s needs. Patients unable to walk without assistance (nonambulatory) were able to walk naturally with the harness, whereas ambulatory patients exhibited improved skilled locomotion such as balance, limb coordination, foot placement, and steering. A clinical trial using this robot-assistive rehabilitation approach for patients with spinal cord injury is currently under way. Gait recovery after neurological disorders requires remastering the interplay between body mechanics and gravitational forces. Despite the importance of gravity-dependent gait interactions and active participation for promoting this learning, these essential components of gait rehabilitation have received comparatively little attention. To address these issues, we developed an adaptive algorithm that personalizes multidirectional forces applied to the trunk based on patient-specific motor deficits. Implementation of this algorithm in a robotic interface reestablished gait dynamics during highly participative locomotion within a large and safe environment. This multidirectional gravity-assist enabled natural walking in nonambulatory individuals with spinal cord injury or stroke and enhanced skilled locomotor control in the less-impaired subjects. A 1-hour training session with multidirectional gravity-assist improved locomotor performance tested without robotic assistance immediately after training, whereas walking the same distance on a treadmill did not ameliorate gait. These results highlight the importance of precise trunk support to deliver gait rehabilitation protocols and establish a practical framework to apply these concepts in clinical routine.

Rehabilitative Soft Exoskeleton for Rodents

Robotic exoskeletons provide programmable, consistent and controllable active therapeutic assistance to patients with neurological disorders. Here we introduce a prototype and preliminary experimental evaluation of a rehabilitative gait exoskeleton that enables compliant yet effective manipulation of the fragile limbs of rats. To assist the displacements of the lower limbs without impeding natural gait movements, we designed and fabricated soft pneumatic actuators (SPAs). The exoskeleton integrates two customizable SPAs that are attached to a limb. This configuration enables a 1 N force load, a range of motion exceeding 80 mm in the major axis, and speed of actuation reaching two gait cycles/s. Preliminary experiments in rats with spinal cord injury validated the basic features of the exoskeleton. We propose strategies to improve the performance of the robot and discuss the potential of SPAs for the design of other wearable interfaces.