A New Test Rig for In-Vitro Evaluation of the Knee Joint Behaviour

The evaluation of the knee joint behavior is fundamental in many applications, such as joint modeling, prosthesis and orthosis design. In-vitro tests are important in order to analyse knee behavior when simulating various loading conditions and studying physiology of the joint. A new test rig for in-vitro evaluation of the knee joint behavior is presented in this paper. It represents the evolution of a previously proposed rig, designed to overcome its principal limitations and to improve its performances. The design procedure and the adopted solution in order to satisfy the specifications are presented here. Thanks to its 6-6 Gough-Stewart parallel manipulator loading system, the rig replicates general loading conditions, like daily actions or clinical tests, on the specimen in a wide range of flexion angles. The restraining actions of knee muscles can be simulated when active actions are simulated. The joint motion in response to the applied loads, guided by passive articular structures and muscles, is permitted by the characteristics of the loading system which is force controlled. The new test rig guarantees visibility so that motion can be measured by an optoelectronic system. Furthermore, the control system of the new test rig allows the estimation of the contribution of the principal leg muscles in guaranteeing the equilibrium of the joint by the system for muscle simulation. Accuracy in positioning is guaranteed by the designed tibia and femur fixation systems,which allow unmounting and remounting the specimen in the same pose. The test rig presented in this paper permits the analysis of the behavior of the knee joint and comparative analysis on the same specimen before and after surgery, in a way to assess the goodness of prostheses or surgical treatments.

Safe and Collaborative Navigation & Interaction With Mobile Manipulators in Domestic Appliance Test Labs

Safe collaboration between a robot and human operator forms a critical requirement for deploying a robotic system into a manufacturing and testing environment. In this dissertation, the safety requirement for is developed and implemented for the navigation system of the mobile manipulators. A methodology for human-robot co-existence through a 3d scene analysis is also investigated. The proposed approach exploits the advance in computing capability by relying on graphic processing units (GPU’s) for volumetric predictive human-robot contact checking. Apart from guaranteeing safety of operators, human-robot collaboration is also fundamental when cooperative activities are required, as in appliance test automation floor. To achieve this, a generalized hierarchical task controller scheme for collision avoidance is developed. This allows the robotic arm to safely approach and inspect the interior of the appliance without collision during the testing procedure. The unpredictable presence of the operators also forms dynamic obstacle that changes very fast, thereby requiring a quick reaction from the robot side. In this aspect, a GPU-accelarated distance field is computed to speed up reaction time to avoid collision between human operator and the robot. An automated appliance testing also involves robotized laundry loading and unloading during life cycle testing. This task involves Laundry detection, grasp pose estimation and manipulation in a container, inside the drum and during recovery grasping. A wrinkle and blob detection algorithms for grasp pose estimation are developed and grasp poses are calculated along the wrinkle and blobs to efficiently perform grasping task. By ranking the estimated laundry grasp poses according to a predefined cost function, the robotic arm attempt to grasp poses that are more comfortable from the robot kinematic side as well as collision free on the appliance side. This is achieved through appliance detection and full-model registration and collision free trajectory execution using online collision avoidance.