Modeling and Simulation of Upper Brachial Plexus Injury

This article presents the first musculoskeletal model and simulation of upper plexus brachial injury. From this model is possible to analyse forces and movement ranges in order to develop a robotic exoskeleton to improve rehabilitation. The software that currently exists for musculoskeletal modeling is varied and most have advanced features for proper analysis and study of motion simulations. Whilst more powerful computer packages are usually expensive, there are other free and open source packages available which offer different tools to perform animations and simulations and which obtain forces and moments of inertia. Among them, Musculoskeletal Modeling Software was selected to construct a model of the upper limb, which has 7 degrees of freedom and 10 muscles. These muscles are important for two of the movements simulated in this article that are part of the post-surgery rehabilitation protocol. We performed different movement animations which are made using the inertial measurement unit to capture real data from movements made by a human being. We also performed the simulation of forces produced in elbow flexion-extension and arm abduction-adduction of a healthy subject and one with upper brachial plexus injury in a postoperative state to compare the force that is capable of being produced in both cases.

A Reliable Open-Source System Architecture for the Fast Designing and Prototyping of Autonomous Multi-UAV Systems: Simulation and Experimentation

During the process of design and development of an autonomous Multi-UAV System, two main problems appear. The first one is the difficulty of designing all the modules and behaviors of the aerial multi-robot system. The second one is the difficulty of having an autonomous prototype of the system for the developers that allows to test the performance of each module even in an early stage of the project. These two problems motivate this paper. A multipurpose system architecture for autonomous multi-UAV platforms is presented. This versatile system architecture can be used by the system designers as a template when developing their own systems. The proposed system architecture is general enough to be used in a wide range of applications, as demonstrated in the paper. This system architecture aims to be a reference for all designers. Additionally, to allow for the fast prototyping of autonomous multi-aerial systems, an Open Source framework based on the previously defined system architecture is introduced. It allows developers to have a flight proven multi-aerial system ready to use, so that they can test their algorithms even in an early stage of the project. The implementation of this framework, introduced in the paper with the name of “CVG Quadrotor Swarm”, which has also the advantages of being modular and compatible with different aerial platforms, can be found at https://​github.​com/​Vision4UAV/​cvg_​quadrotor_​swarm with a consistent catalog of available modules. The good performance of this framework is demonstrated in the paper by choosing a basic instance of it and carrying out simulation and experimental tests whose results are summarized and discussed in this paper.

A Vision-based Quadrotor Multi-robot Solution for the Indoor Autonomy Challenge of the 2013 International Micro Air Vehicle Competition

This paper presents a completely autonomous solution to participate in the Indoor Challenge of the 2013 International Micro Air Vehicle Competition (IMAV 2013). Our proposal is a multi-robot system with no centralized coordination whose robotic agents share their position estimates. The capability of each agent to navigate avoiding collisions is a consequence of the resulting emergent behavior. Each agent consists of a ground station running an instance of the proposed architecture that communicates over WiFi with an AR Drone 2.0 quadrotor. Visual markers are employed to sense and map obstacles and to improve the pose estimation based on Inertial Measurement Unit (IMU) and ground optical flow data. Based on our architecture, each robotic agent can navigate avoiding obstacles and other members of the multi-robot system. The solution is demonstrated and the achieved navigation performance is evaluated by means of experimental flights. This work also analyzes the capabilities of the presented solution in simulated flights of the IMAV 2013 Indoor Challenge. The performance of the CVG UPM team was awarded with the First Prize in the Indoor Autonomy Challenge of the IMAV 2013 competition.