Iterative learning control method for improving the effectiveness of upper limb rehabilitation

In rehabilitation, passive control mode is common used at early stages of the post-stroke therapy, when the impaired limb is usually unresponsive. The simplest is the use of a proportional-integral-derivative (PID) feedback control which usually regulates the position or the interaction force along a known reference. Nonetheless PID method cannot achieve an ideal tracking performance due to dynamical uncertainties and unknown time-varying periodic disturbances from the environment. In order to minimize steady-state error with respect to uncertainties in exoskeleton passive control, Iterative Learning Control(ILC) and Neural PID control are proposed to improve the control effective of conventional linear PID. In this paper, two different control algorithms are introduced. Moreover, an experimental study on a 5-DOF upper limb exoskeleton with them is addressed for comparison

Design, implementation, control, and user evaluations of assiston-arm self-aligning upper-extremity exoskeleton

Physical rehabilitation therapy is indispensable for treating neurological disabilities. The use of robotic devices for rehabilitation holds high promise, since these devices can bear the physical burden of rehabilitation exercises during intense therapy sessions, while therapists are employed as decision makers. Robot-assisted rehabilitation devices are advantageous as they can be applied to patients with all levels of impairment, allow for easy tuning of the duration and intensity of therapies and enable customized, interactive treatment protocols. Moreover, since robotic devices are particularly good at repetitive tasks, rehabilitation robots can decrease the physical burden on therapists and enable a single therapist to supervise multiple patients simultaneously; hence, help to lower cost of therapies. While the intensity and quality of manually delivered therapies depend on the skill and fatigue level of therapists, high-intensity robotic therapies can always be delivered with high accuracy. Thanks to their integrated sensors, robotic devices can gather measurements throughout therapies, enable quantitative tracking of patient progress and development of evidence-based personalized rehabilitation programs. In this dissertation, we present the design, control, characterization and user evaluations of AssistOn-Arm, a powered, self-aligning exoskeleton for robotassisted upper-extremity rehabilitation. AssistOn-Arm is designed as a passive back-driveable impedance-type robot such that patients/therapists can move the device transparently, without much interference of the device dynamics on natural movements. Thanks to its novel kinematics and mechanically transparent design, AssistOn-Arm can passively self-align its joint axes to provide an ideal match between human joint axes and the exoskeleton axes, guaranteeing ergonomic movements and comfort throughout physical therapies. The self-aligning property of AssistOn-Arm not only increases the usable range of motion for robot-assisted upper-extremity exercises to cover almost the whole human arm workspace, but also enables the delivery of glenohumeral mobilization (scapular elevation/depression and protraction/retraction) and scapular stabilization exercises, extending the type of therapies that can be administered using upper-extremity exoskeletons. Furthermore, the self-alignment property of AssistOn-Arm signi cantly shortens the setup time required to attach a patient to the exoskeleton. As an impedance-type device with high passive back-driveability, AssistOn- Arm can be force controlled without the need of force sensors; hence, high delity interaction control performance can be achieved with open-loop impedance control. This control architecture not only simpli es implementation, but also enhances safety (coupled stability robustness), since open-loop force control does not su er from the fundamental bandwidth and stability limitations of force-feedback. Experimental characterizations and user studies with healthy volunteers con- rm the transparency, range of motion, and control performance of AssistOn- Ar

Redundant Unilaterally Actuated Kinematic Chains: Modeling and Analysis

Unilaterally Actuated Robots (UAR)s are a class of robots defined by an actuation that is constrained to a single sign. Cable robots, grasping, fixturing and tensegrity systems are certain applications of UARs. In recent years, there has been increasing interest in robotic and other mechanical systems actuated or constrained by cables. In such systems, an individual constraint is applied to a body of the mechanism in the form of a pure force which can change its magnitude but cannot reverse its direction. This uni-directional actuation complicates the design of cable-driven robots and can result in limited performance. Cable Driven Parallel Robot (CDPR)s are a class of parallel mechanisms where the actuating legs are replaced by cables. CDPRs benefit from the higher payload to weight ratio and increased rigidity. There is growing interest in the cable actuation of multibody systems. There are potential applications for such mechanisms where low moving inertia is required. Cable-driven serial kinematic chain (CDSKC) are mechanisms where the rigid links form a serial kinematic chain and the cables are arranged in a parallel configuration. CDSKC benefits from the dexterity of the serial mechanisms and the actuation advantages of cable-driven manipulators. Firstly, the kinematic modeling of CDSKC is presented, with a focus on different types of cable routings. A geometric approach based on convex cones is utilized to develop novel cable actuation schemes. The cable routing scheme and architecture have a significant effect on the performance of the robot resulting in a limited workspace and high cable forces required to perform a desired task. A novel cable routing scheme is proposed to reduce the number of actuating cables. The internal routing scheme is where, in addition to being externally routed, the cable can be re-routed internally within the link. This type of routing can be considered as the most generalized form of the multi-segment pass-through routing scheme where a cable segment can be attached within the same link. Secondly, the analysis for CDSKCs require extensions from single link CDPRs to consider different routings. The conditions to satisfy wrench-closure and the workspace analysis of different multi-link unilateral manipulators are investigated. Due to redundant and constrained actuation, it is possible for a motion to be either infeasible or the desired motion can be produced by an infinite number of different actuation profiles. The motion generation of the CDSKCs with a minimal number of actuating cables is studied. The static stiffness evaluation of CDSKCs with different routing topologies and isotropic stiffness conditions were investigated. The dexterity and wrench-based metrics were evaluated throughout the mechanism's workspace. Through this thesis, the fundamental tools required in studying cable-driven serial kinematic chains have been presented. The results of this work highlight the potential of using CDSKCs in bio-inspired systems and tensegrity robots

Kinematics and Robot Design IV, KaRD2021

This volume collects the papers published on the special issue “Kinematics and Robot Design IV, KaRD2021” (https://www.mdpi.com/journal/robotics/special_issues/KaRD2021), which is the forth edition of the KaRD special-issue series, hosted by the open-access journal “MDPI Robotics”. KaRD series is an open environment where researchers can present their works and discuss all the topics focused on the many aspects that involve kinematics in the design of robotic/automatic systems. Kinematics is so intimately related to the design of robotic/automatic systems that the admitted topics of the KaRD series practically cover all the subjects normally present in well-established international conferences on “mechanisms and robotics”. KaRD2021, after the peer-review process, accepted 12 papers. The accepted papers cover some theoretical and many design/applicative aspects

Modular and Analytical Methods for Solving Kinematics and Dynamics of Series-Parallel Hybrid Robots

While serial robots are known for their versatility in applications, larger workspace, simpler modeling and control, they have certain disadvantages like limited precision, lower stiffness and poor dynamic characteristics in general. A parallel robot can offer higher stiffness, speed, accuracy and payload capacity, at the downside of a reduced workspace and a more complex geometry that needs careful analysis and control. To bring the best of the two worlds, parallel submechanism modules can be connected in series to achieve a series-parallel hybrid robot with better dynamic characteristics and larger workspace. Such a design philosophy is being used in several robots not only at DFKI (for e.g., Mantis, Charlie, Recupera Exoskeleton, RH5 humanoid etc.) but also around the world, for e.g. Lola (TUM), Valkyrie (NASA), THOR (Virginia Tech.) etc.These robots inherit the complexity of both serial and parallel architectures. Hence, solving their kinematics and dynamics is challenging because they are subjected to additional geometric loop closure constraints. Most approaches in multi-body dynamics adopt numerical resolution of these constraints for the sake of generality but may suffer from inaccuracy and performance issues. They also do not exploit the modularity in robot design. Further, closed loop systems can have variable mobility, different assembly modes and can impose redundant constraints on the equations of motion which deteriorates the quality of many multi-body dynamics solvers. Very often only a local view to the system behavior is possible. Hence, it is interesting for geometers or kinematics researchers, to study the analytical solutions to geometric problems associated with a specific type of parallel mechanism and their importance over numerical solutions is irrefutable. Techniques such as screw theory, computational algebraic geometry, elimination and continuation methods are popular in this domain. But this domain specific knowledge is often underrepresented in the design of model based kinematics and dynamics software frameworks. The contributions of this thesis are two-fold. Firstly, a rigorous and comprehensive kinematic analysis is performed for the novel parallel mechanisms invented recently at DFKI-RIC such as RH5 ankle mechanism and Active Ankle using approaches from computational algebraic geometry and screw theory. Secondly, the general idea of a modular software framework called Hybrid Robot Dynamics (HyRoDyn) is presented which can be used to solve the geometry, kinematics and dynamics of series-parallel hybrid robotic systems with the help of a software database which stores the analytical solutions for parallel submechanism modules in a configurable and unit testable manner. HyRoDyn approach is suitable for both high fidelity simulations and real-time control of complex series-parallel hybrid robots. The results from this thesis has been applied to two robotic systems namely Recupera-Reha exoskeleton and RH5 humanoid. The aim of this software tool is to assist both designers and control engineers in developing complex robotic systems of the future. Efficient kinematic and dynamic modeling can lead to more compliant behavior, better whole body control, walking and manipulating capabilities etc. which are highly desired in the present day and future robotic applications

A novel method for the characterisation of human upper limb workspace with respect to dexterity

Human dexterity is a complex phenomenon associated to physiological and cognitive factors that affect the execution of precise movements. Dexterity is strongly linked to upper limb (UL) functionality and performance, and its study is important for clinical analysis, ergonomics, sports biomechanics, design, rehabilitation, and human-machine interactions. However, its understanding is quite limited. Dexterity is commonly assessed through time-dependent dexterity tests that can determine the successful completion of tasks on test boards paced in front of the participant. However, such tests cannot inform about participant performance in other regions of the corresponding UL workspace volume (WV), and they can only collect data related to specific tasks, and therefore, cannot predict UL performance for the execution of other tasks. This thesis establishes a time-independent novel method for the characterisation of UL workspace with respect to dexterity; the “Dexterity Analysis Method” (DAM), which is based on the manipulability analysis method (used in robotics to quantify robot manipulability). The DAM is flexible, versatile, and scalable. It can be used to analyse real and virtual individuals or populations using direct measures or statistical data. Moreover, the DAM allows adding human factors, and to assigning their weights for adjustment and calibration. Hence, the DAM is a powerful tool that can help to evaluate performance, assess healthiness, optimise implants and prosthetics, design ergonomic workplaces and homes, develop assistive devices, and conduct pre- and post-surgery evaluations. Moreover, this work, as implemented in the DAM, promotes the use of WV as an objective reference to map performance, healthiness, and dexterity. Finally, the DAM contributes to closing the knowledge gaps on the understanding and quantification of UL motion, workspace, and dexterity. However, the DAM still needs to be fully validated as the experimental results obtained in this research with such purpose were not conclusive. A real-life application of the DAM is illustrated in Chapter 7 of this work, which analyses the effects of reverse shoulder arthroplasty (RSA) on WV and dexterity. The results indicate that WV for healthy people can be around 32% larger than those for people with RSA. However, it was found that greater WV do not necessarily translate into larger high dexterity regions, and the effects of reductions in ROM on WV depend on the extreme at which such reductions occur. For instance, a decrease of 15° in elbow extension reduces 2% of 2-D reachability, whereas a decrease of 15° in elbow flexion only reduces it by 10.8%. Therefore, surgeons should carefully consider such factors when making decisions during joint surgery, reconstruction, and implant position optimisation