Physical simulation for monocular 3D model based tracking

The problem of model-based object tracking in three dimensions is addressed. Most previous work on tracking assumes simple motion models, and consequently tracking typically fails in a variety of situations. Our insight is that incorporating physics models of object behaviour improves tracking performance in these cases. In particular it allows us to handle tracking in the face of rigid body interactions where there is also occlusion and fast object motion. We show how to incorporate rigid body physics simulation into a particle filter. We present two methods for this based on pose and force noise. The improvements are tested on four videos of a robot pushing an object, and results indicate that our approach performs considerably better than a plain particle filter tracker, with the force noise method producing the best results over the range of test videos

Asymmetric Dual-Arm Task Execution using an Extended Relative Jacobian

Coordinated dual-arm manipulation tasks can be broadly characterized as possessing absolute and relative motion components. Relative motion tasks, in particular, are inherently redundant in the way they can be distributed between end-effectors. In this work, we analyse cooperative manipulation in terms of the asymmetric resolution of relative motion tasks. We discuss how existing approaches enable the asymmetric execution of a relative motion task, and show how an asymmetric relative motion space can be defined. We leverage this result to propose an extended relative Jacobian to model the cooperative system, which allows a user to set a concrete degree of asymmetry in the task execution. This is achieved without the need for prescribing an absolute motion target. Instead, the absolute motion remains available as a functional redundancy to the system. We illustrate the properties of our proposed Jacobian through numerical simulations of a novel differential Inverse Kinematics algorithm.Comment: Accepted for presentation at ISRR19. 16 Page

Quantifying the Evolutionary Self Structuring of Embodied Cognitive Networks

We outline a possible theoretical framework for the quantitative modeling of networked embodied cognitive systems. We notice that: 1) information self structuring through sensory-motor coordination does not deterministically occur in Rn vector space, a generic multivariable space, but in SE(3), the group structure of the possible motions of a body in space; 2) it happens in a stochastic open ended environment. These observations may simplify, at the price of a certain abstraction, the modeling and the design of self organization processes based on the maximization of some informational measures, such as mutual information. Furthermore, by providing closed form or computationally lighter algorithms, it may significantly reduce the computational burden of their implementation. We propose a modeling framework which aims to give new tools for the design of networks of new artificial self organizing, embodied and intelligent agents and the reverse engineering of natural ones. At this point, it represents much a theoretical conjecture and it has still to be experimentally verified whether this model will be useful in practice.

The dynamic control of robotic manipulators in space

Described briefly is the work done during the first half year of a three-year study on dynamic control of robotic manipulators in space. The research focused on issues for advanced control of space manipulators including practical issues and new applications for the Virtual Manipulator. In addition, the development of simulations and graphics software for space manipulators, begun during the first NASA proposal in the area, has continued. The fabrication of the Vehicle Emulator System (VES) is completed and control algorithms are in process of development

Decentralized collaborative transport of fabrics using micro-UAVs

Small unmanned aerial vehicles (UAVs) have generally little capacity to carry payloads. Through collaboration, the UAVs can increase their joint payload capacity and carry more significant loads. For maximum flexibility to dynamic and unstructured environments and task demands, we propose a fully decentralized control infrastructure based on a swarm-specific scripting language, Buzz. In this paper, we describe the control infrastructure and use it to compare two algorithms for collaborative transport: field potentials and spring-damper. We test the performance of our approach with a fleet of micro-UAVs, demonstrating the potential of decentralized control for collaborative transport.Comment: Submitted to 2019 International Conference on Robotics and Automation (ICRA). 6 page

NAOMOBBY, desarrollo de una herramienta software basada en visión por computador y robótica para apoyar la rehabilitación en terapias físicas de miembros superiores

Nowadays, 21% of Colombian population, and the 35% of the population in Cauca Valley have limited movement of body, arms, hands or legs. Then, the quality of life of these people is highly affected, since they have limitations in daily living activities. Physical rehabilitation therapies allow the restoration of movement and maximum functional capacity in people. Successful physical therapies depend on empathy and motivation with the rehabilitation process (RP), then the more empathy of patients with the RP, the more patient willingness regarding the rehabilitation therapy. Motivation is crucial in rehabilitation, and it is used as a fundamental rehabilitation out-come. This work has the aim to present the software tool called NAOMOBBY to support physical rehabilitation therapies of shoulder, elbow and wrist joints. NAOMOBBY includes a GUI for therapist, a Kinect sensor and an interactive humanoid robot NAO to increase the patient willingness regarding the RP. NAOMOBBY includes the following modules: configuration/management, movement reproduction, and results report using GAS methodology. NAOMOBBY was tested using quantitative and field tests. Quantitative tests measure the error in the Kinect sensor of the NAO robot joint motions to bring users a suitable feedback. Quantitative results were obtained using three basic functional motions. The mean square error for these three motions were 0,373%, 0,096%, and 1,129% respectively. Field tests were conducted at the SURGIR neuro-rehabilitation center using 3 physiotherapists who considered the NAOMOBBY software tool as a novel, easy to use, and that encourage patients to perform the physical therapy.Actualmente, el 21% de la población en Colombia y el 35% de la población del Valle del Cauca tiene limitaciones en el movimiento del cuerpo, brazos, manos o piernas. Entonces, la calidad de vida de estas personas está altamente afectado, ya que ellas tienen limitaciones al desarrollar actividades del diario vivir. La rehabilitación a través de la terapia física, permite la restauración del movimiento y la máxima capacidad funcional en las personas. Terapias físicas exitosas dependen de la empatía y motivación con el proceso de rehabilitación (PR), entonces entre más alta la empatía de los pacientes con el PR, más alta la disposición será de los pacientes en relación con la terapia de rehabilitación. Motivación es crucial en rehabilitación, y es usado como un resultado determinante de la rehabilitación. Este trabajo tiene el objetivo de presentar la herramienta software llamada NAOMOBBY para soportar las terapias de rehabilitación física de las articulaciones de hombro, codo y muñeca. NAOMOBBY incluye una GUI para terapeutas, un sensor Kinect y un robot interactivo humanoide NAO con el fin de incrementar la disposición del paciente hacia el PR. NAOMOBBY incluye los siguientes módulos: configuración y gestión, reproducción de movimiento y reporte de resultados usando la metodología GAS. NAOMOBBY fue probada usando pruebas cuantitativas y de campo. Las pruebas cuantitativas miden el error en el sensor Kinect de los movimientos de las articulaciones del robot NAO, con el fin de brindar a los usuarios una adecuada realimentación. Los resultados cuantitativos fueron obtenidos usando tres movimientos funcionales básicos. Los errores cuadráticos medios de estos tres movimientos fueron 0,373%, 0,096%, y 1,129% respectivamente. Las pruebas de campo fueron realizadas en el centro de neuro-rehabilitación SURGIR usando 3 fisioterapeutas quienes consideraron a la herramienta software NAOMOBBY como novedosos, fáciles de usar y que motiva a los pacientes a realizar la terapia física