Symmetric Kullback-Leibler Metric Based Tracking Behaviors for Bioinspired Robotic Eyes

A symmetric Kullback-Leibler metric based tracking system, capable of tracking moving targets, is presented for a bionic spherical parallel mechanism to minimize a tracking error function to simulate smooth pursuit of human eyes. More specifically, we propose a real-time moving target tracking algorithm which utilizes spatial histograms taking into account symmetric Kullback-Leibler metric. In the proposed algorithm, the key spatial histograms are extracted and taken into particle filtering framework. Once the target is identified, an image-based control scheme is implemented to drive bionic spherical parallel mechanism such that the identified target is to be tracked at the center of the captured images. Meanwhile, the robot motion information is fed forward to develop an adaptive smooth tracking controller inspired by the Vestibuloocular Reflex mechanism. The proposed tracking system is designed to make the robot track dynamic objects when the robot travels through transmittable terrains, especially bumpy environment. To perform bumpy-resist capability under the condition of violent attitude variation when the robot works in the bumpy environment mentioned, experimental results demonstrate the effectiveness and robustness of our bioinspired tracking system using bionic spherical parallel mechanism inspired by head-eye coordination

Inertial measurement units: a brief state of the art on gait analysis

Gait analysis systems are monitoring systems that establish a symbiosis relationship with Ambient Assisted Living (AAL) environments. Human locomotion analysis has a very important role always aiming at improving the quality of life both for individuals needing treatment or rehabilitation, as well as for healthy and elderly people. In fact, a deep and detailed knowledge about gait characteristics at a given time, and not least, monitoring and evaluating over time, will allow early diagnosis of diseases and their complications, and contribute to the decision of the treatment that should be chosen. There are several techniques used for gait measuring such as: Image Processing, Floor Sensors, and Wearable Sensors. Among the wearable sensors, has emerged an electronic device that combines multiple sensors designated by Inertial Measurement Unit (IMU). This device measures angular rate, body's specific force, and in some cases the magnetic field, and this information may be used to monitor human gait. In this article, the aim is: i) to verify the sensors that build up the IMUs, and the resulting designations that the device may have depending on the sensors it contains; ii) to list the applications of the IMUs on gait analysis; iii) to be aware of the devices available on the market and the associated commercial brands; and iv) to list the advantages and disadvantages associated with the device compared to other gait analysis systems. Concerning the literature in the scientific community, although there are some studies that focus on gait analysis or IMUs, none of them aggregates the purposes that will be addressed in this article.This work is supported by the FCT - Fundação para a Ciência e Tecnologia - with the scholarship reference SFRH/BD/108309/2015, with the reference project UID/EEA/04436/2013, by FEDER funds through the COMPETE 2020 - Programa Operacional Competitividade e Internacionalização (POCI) - with the reference project POCI-01-0145- FEDER-006941

CUPH: A Synergistic aquatic camera design

None provided

人間を模擬した知覚系を持つ2足ヒューマノイドロボットの自己位置推定機能に対する歩行動作の影響に関する研究

早大学位記番号:新8279早稲田大

An Architecture for Online Affordance-based Perception and Whole-body Planning

The DARPA Robotics Challenge Trials held in December 2013 provided a landmark demonstration of dexterous mobile robots executing a variety of tasks aided by a remote human operator using only data from the robot's sensor suite transmitted over a constrained, field-realistic communications link. We describe the design considerations, architecture, implementation and performance of the software that Team MIT developed to command and control an Atlas humanoid robot. Our design emphasized human interaction with an efficient motion planner, where operators expressed desired robot actions in terms of affordances fit using perception and manipulated in a custom user interface. We highlight several important lessons we learned while developing our system on a highly compressed schedule

A Continuous Grasp Representation for the Imitation Learning of Grasps on Humanoid Robots

Models and methods are presented which enable a humanoid robot to learn reusable, adaptive grasping skills. Mechanisms and principles in human grasp behavior are studied. The findings are used to develop a grasp representation capable of retaining specific motion characteristics and of adapting to different objects and tasks. Based on the representation a framework is proposed which enables the robot to observe human grasping, learn grasp representations, and infer executable grasping actions

How accurate are the fusion of Cone-beam CT and 3-D stereophotographic images?

Background: Cone-beam Computed Tomography (CBCT) and stereophotography are two of the latest imaging modalities available for three-dimensional (3-D) visualization of craniofacial structures. However, CBCT provides only limited information on surface texture. This can be overcome by combining the bone images derived from CBCT with 3-D photographs. The objectives of this study were 1) to evaluate the feasibility of integrating 3-D Photos and CBCT images 2) to assess degree of error that may occur during the above processes and 3) to identify facial regions that would be most appropriate for 3-D image registration. Methodology: CBCT scans and stereophotographic images from 29 patients were used for this study. Two 3-D images corresponding to the skin and bone were extracted from the CBCT data. The 3-D photo was superimposed on the CBCT skin image using relatively immobile areas of the face as a reference. 3-D colour maps were used to assess the accuracy of superimposition were distance differences between the CBCT and 3-D photo were recorded as the signed average and the Root Mean Square (RMS) error. Principal Findings: The signed average and RMS of the distance differences between the registered surfaces were -0.018 (±0.129) mm and 0.739 (±0.239) mm respectively. The most errors were found in areas surrounding the lips and the eyes, while minimal errors were noted in the forehead, root of the nose and zygoma. Conclusions: CBCT and 3-D photographic data can be successfully fused with minimal errors. When compared to RMS, the signed average was found to under-represent the registration error. The virtual 3-D composite craniofacial models permit concurrent assessment of bone and soft tissues during diagnosis and treatment planning. © 2012 Jayaratne et al.published_or_final_versio

Estimação de verticalidade e estabilização de uma cabeça humanóide

Mestrado em Engenharia MecânicaO Projeto Humanóide da Universidade de Aveiro (PHUA) é a base desta dissertação que tem como objetivo estudar a estabilização da cabeça de um robô humanóide para efeitos de equilíbrio. Foram assim desenvolvidas soluções integradas usando o Robot Operating System (ROS). Para estabilizar a cabeça humanóide, foi estimado o vetor da gravidade (verticalidade) usando dados visuais. Para o fazer, duas soluções distintas foram abordadas, ambas baseadas na biblioteca Visual Servoing Platform (ViSP). Depois de estimada a verticalidade, a cabeça humanóide (uma câmara montada numa unidade roll-tilt) foi estabilizada recorrendo a um controlador proporcionalderivativo (PD) de posição para o servomotor responsável pelo ângulo roll e a um controlo PD de velocidade para o servomotor responsável pelo ângulo tilt. Para fazer as experiências, o sistema foi montado num manipulador robótico para permitir repetibilidade e controlo preciso de movimentos. A análise dos resultados das experiências mostra que quer a estimação da verticalidade quer a estabilização da cabeça humanóide foram tarefas realizadas com sucesso. Esta análise permite também concluir que a taxa de aquisição de imagem influencia os resultados, e que a limitada taxa do sistema usado (cerca de 15 imagens por segundo) condicionou um pouco a robustez dos resultados em situações mais exigentes.The Humanoid Project of the University of Aveiro (PHUA) is the basis of this dissertation, whose purpose is to study the effects of the stabilization of a humanoid head in obtaining its equilibrium. Therefore, integrated solutions using the Robot Operating System (ROS) were developed. To stabilize the humanoid head, the gravity vector (verticality) was estimated using visual data. In order to do so, two distinct solutions were approached, both based on the Visual Servoing Platform (ViSP) library. After estimating verticality, the humanoid head (a camera mounted on a roll-tilt unit) was stabilized using a proportional-derivative (PD) controller for the position of the servo responsible for the roll angle and a PD controller for the velocity of the servomotor responsible for the tilt angle. To perform the experiments, the system was mounted on a robotic manipulator to allow repeatability and precise movement control. An analysis to the experiment results shows that both the verticality estimation and head stabilization tasks were performed successfully. This analysis also allows for the conclusion that the image frame rate influences results, and that the limited frame rate of the system used (about 15 frames per second) slightly conditioned the robustness of results in more demanding scenarios