A Bio-Inspired Tensegrity Manipulator with Multi-DOF, Structurally Compliant Joints

Most traditional robotic mechanisms feature inelastic joints that are unable to robustly handle large deformations and off-axis moments. As a result, the applied loads are transferred rigidly throughout the entire structure. The disadvantage of this approach is that the exerted leverage is magnified at each subsequent joint possibly damaging the mechanism. In this paper, we present two lightweight, elastic, bio-inspired tensegrity robotics arms which mitigate this danger while improving their mechanism's functionality. Our solutions feature modular tensegrity structures that function similarly to the human elbow and the human shoulder when connected. Like their biological counterparts, the proposed robotic joints are flexible and comply with unanticipated forces. Both proposed structures have multiple passive degrees of freedom and four active degrees of freedom (two from the shoulder and two from the elbow). The structural advantages demonstrated by the joints in these manipulators illustrate a solution to the fundamental issue of elegantly handling off-axis compliance.Comment: IROS 201

Felső végtag kinematikai modelljének rekonstrukciója kétkaros rehabilitációs robot szerszámkoordináta-rendszerei alapján: Tool center point frame based reconstruction of the upper limb kinematic model in a dual-arm rehabilitation robot scenario

During the rehabilitation of upper limb function loss caused by stroke, the reconstruction of the kinematic model of the limb is the basis for the automatic assessment of patients and the personalization of robotic physiotherapy exercises. The aim is to determine the permanent anatomical parameters of the model: forearm, upper arm and hand lengths, the variable anatomical parameters: shoulder, elbow, wrist positions, and then the anatomical angles. The kinematic model reconstruction presented here does not require prior manual measurement or external sensors data, only the data of the tool coordinate systems of each robotic arm connected to the forearm and hand via the elbow and hand orthoses. First, the reconstruction algorithm of the model is presented in a plane, in two dimensions, which is verified by a virtual limb model created in a CAD system. We then extend the reconstruction algorithm to three dimensions. The mathematical calculations are performed in Wolfram Mathematica system. Kivonat A stroke miatt bekövetkezett felső végtagi funkcióvesztés robotos gyógytornáztatással történő rehabilitációja során a végtag kinematikai modelljének rekonstrukciója a betegek automatikus állapotfelmérésének és a robotos gyógytorna gyakorlatok személyre szabásának alapja. A célul kitűzött feladat a modell állandó anatómiai paramétereinek: az alkar, a felkar, és a kézfej hosszának, valamint a változó anatómiai paramétereinek: a váll, a könyök, a csukló helyzetének, majd belőlük az anatómiai szögeknek a meghatározása. A bemutatott kinematikai modell rekonstrukcióhoz nincs szükség előzetes manuális felmérés vagy külső érzékelők által szolgáltatott adatokra, kizárólag az alkarhoz és kézfejhez a könyök, illetve kézfej ortéziseken keresztül csatlakozó egy-egy robotkar szerszámkoordináta-rendszereinek az adataira. Először síkban, két dimenzióban kerül bemutatásra a modell rekonstrukciós algoritmusa, amelyet CAD rendszerben előállított virtuális végtagmodellel ellenőrzünk. Ezt követően kiterjesztjük a rekonstrukciós algoritmust három dimenzióra. A matematikai számításokat Wolfram Mathematica rendszerben hajtjuk végre. &nbsp

Design, analysis and fabrication of an articulated mobile manipulator

The process involved in designing, fabricating and analysing a mobile robotic manipulator to carry out pick and place task in a dynamic and unknown environment has been explained here. The manipulator designed and fabricated has a 5 – axis articulated arm for pick and place application but also can be reconfigured to do other tasks. The manipulator is built with its driving or power means fitted at the bottom to distribute the load effectively and also make handling easier. The mobile platform employs a novel suspension system which helps in relatively distributing the load equally to all wheels regardless of the wheels position giving the mobile platform better control and stability. With reference to many available manipulators and mobile platforms in the market, a practical design is perceived using designing tools and a fully functional prototype is fabricated. The kinematic model determining the end effector’s position and orientation is analysed systematically and presented. Navigational controls are built using fuzzy logic and genetic algorithm with the help of the sensors’ information so that the robot can negotiate obstacle while carrying out various tasks in an unknown environment. The path tracking for pick-and-place application is the overall target of this industrial manipulator

Methods and good practice guidelines for human joint kinematics estimation through magnetic and inertial wearable sensors

According to the World Health Organization, the ability to move is recognized as a key factor for the human well-being. From the wearable Magnetic and Inertial Measurement Units (MIMUs) signals it is possible to extract several digital mobility outcomes including the joint kinematics. To this end, it is first required to estimate the orientation of the MIMUs by means of a sensor fusion algorithm (SFA). After that, the relative orientation is computed and then decomposed to obtain the joint angles. However, the MIMUs do not provide a direct output of the physical quantity of interest which can be only determined after an ad hoc processing of their signals. It follows that the joint angle accuracy mostly depends on multiple factors. The first one is the magnitude of the MIMU measurements errors and up to date there is still a lack of methods for their characterization. A second crucial factor is the choice of the SFA to use. Despite the abundance of formulations in the literature, no-well established conclusions about their accuracy have been reached yet. The last factor is the biomechanical model used to compute the joint angles. In this context, unconstrained methods offer a simple way to decompose the relative orientation using the Euler angles but suffer from the inherent issues related to the SFA. In contrast, constrained approaches aim at increasing the robustness of the estimates by adopting models in which an objective function is minimized through the definition of physiological constraints. This thesis proposed the methods to accurately estimate the human joint kinematics starting from the MIMU signals. Three main contributions were provided. The first consisted in the design of a comprehensive battery of tests to completely characterize the sources of errors affecting the quality of the measurements. These tests rely on simple hypotheses based on the sensor working principles and do not require expensive equipment. Nine parameters were defined to quantify the signal accuracy improvements (if any) of 24 MIMUs before and after the refinement of their calibration coefficients. The second contribution was focused on the SFAs. Ten among the most popular SFAs were compared under different experimental conditions including different MIMU models and rotation rate magnitudes. To perform a “fair” comparison it was necessary to set the optimal parameter values for each SFA. The most important finding was that all the errors fall within a range from 3.8 deg to 7.1 deg thus making it impossible to draw any conclusions about the best performing SFA since no statistically significant differences were found. In addition, the orientation accuracy was heavily influenced by the experimental variables. After that, a novel method was designed to estimate the suboptimal parameter values of a given SFA without relying on any orientation reference. The maximum difference between the errors obtained using optimal and suboptimal parameter values amounted to 3.7 deg and to 0.6 deg on average. The last contribution consisted in the design of an unconstrained and a constrained methods for estimating the joint kinematics without considering the magnetometer to avoid the ferromagnetic disturbances. The unconstrained method was employed in a telerehabilitation platform in which the joint angles were estimated in real time. Errors collected during the execution of a full-body protocol were lower than 5 deg (considered the acceptability threshold). However, this method may be inaccurate after few minutes since no solutions can be taken to mitigate the drift error. To overcome this limitation a constrained method was developed based on a robotic model of the upper limb to set appropriate constraints. Errors relative to a continuous robot motion for twenty minutes were lower than 3 deg at most suggesting the feasibility of employing these solutions in the rehabilitation programs to properly plan the treatment and to accurately evaluate the outcomes

Experimental Study on Human Arm Reaching with and without a Reduced Mobility for Applications in Medical Human-Interactive Robotics

Along with increasing advances in robotic technologies, there are now significant efforts under way to improve the quality of life especially those with physical disabilities or impairments. Control of such medical human-interactive robotics (HIR) involves complications in its design and control due to uncertain human factors. This dissertation makes its efforts to resolve three main challenges of an advanced HIR controller development: 1) detecting the operator’s motion intent, 2) understanding human motor behavior from the robotic perspective, and 3) generating reference motion for the HIR. Our interests in such challenges are limited to the point-to-point reaching of the human arm for applications of their solutions in the control of rehabilitation exoskeletons, therapeutic haptic devices, and prosthetic arms. In the context of human motion intent detection, a mobile motion capture system (MCS) enhanced with myoprocessors is developed to capture kinematics and dynamics of human arm in reaching movements. The developed MCS adopts wireless IMU (inertial measurement unit) sensors to capture ADL (activities of daily life) motions in the real-life environment. In addition, measured muscle activation patterns from selected muscle groups are converted into muscular force values by myoprocessors. This allows a reliable motion intent detection by quantify one of the most frequently used driving signal of the HIR, EMG (electromyography), in a standardized way. In order to understand the human motor behavior from the robotic viewpoint, a computational model on reaching is required. Since such model can be constituted by experimental observations, this dissertation look into invariant motion features of reaching with and without elbow constraint condition to establish a foundation of the computational model. The HIR should generate its reference motions by reflecting motor behavior of the natural human reaching. Though the accurate approximation of such behavior is critical, we also need to take into account the computational cost, especially for real-time applications such as the HIR control. In this manner, a higher order kinematic synthesis of mechanical linkage systems is adopted to approximate natural human hand profiles. Finally, a novel control concept of a myo-prosthetic arm is proposed as an application of all findings and efforts made in this dissertation