Spatial context-aware person-following for a domestic robot

Domestic robots are in the focus of research in terms of service providers in households and even as robotic companion that share the living space with humans. A major capability of mobile domestic robots that is joint exploration of space. One challenge to deal with this task is how could we let the robots move in space in reasonable, socially acceptable ways so that it will support interaction and communication as a part of the joint exploration. As a step towards this challenge, we have developed a context-aware following behav- ior considering these social aspects and applied these together with a multi-modal person-tracking method to switch between three basic following approaches, namely direction-following, path-following and parallel-following. These are derived from the observation of human-human following schemes and are activated depending on the current spatial context (e.g. free space) and the relative position of the interacting human. A combination of the elementary behaviors is performed in real time with our mobile robot in different environments. First experimental results are provided to demonstrate the practicability of the proposed approach

Information acquisition using eye-gaze tracking for person-following with mobile robots

In the effort of developing natural means for human-robot interaction (HRI), signifcant amount of research has been focusing on Person-Following (PF) for mobile robots. PF, which generally consists of detecting, recognizing and following people, is believed to be one of the required functionalities for most future robots that share their environments with their human companions. Research in this field is mostly directed towards fully automating this functionality, which makes the challenge even more tedious. Focusing on this challenge leads research to divert from other challenges that coexist in any PF system. A natural PF functionality consists of a number of tasks that are required to be implemented in the system. However, in more realistic life scenarios, not all the tasks required for PF need to be automated. Instead, some of these tasks can be operated by human operators and therefore require natural means of interaction and information acquisition. In order to highlight all the tasks that are believed to exist in any PF system, this paper introduces a novel taxonomy for PF. Also, in order to provide a natural means for HRI, TeleGaze is used for information acquisition in the implementation of the taxonomy. TeleGaze was previously developed by the authors as a means of natural HRI for teleoperation through eye-gaze tracking. Using TeleGaze in the aid of developing PF systems is believed to show the feasibility of achieving a realistic information acquisition in a natural way

Person Detection and Tracking Using Binocular Lucas-Kanade Feature Tracking and K-means Clustering

In this thesis, we present the design and implementation of a method for real-time person detection and tracking. Many current methods for detecting and tracking people rely on color contrast or movement to segment the image. Using color, however, requires the target and the background to be significantly different, and motion segmentation requires the target to be in constant motion relative to the background, often requiring stationary cameras. Pattern detection methods have also been applied to the problem of detecting pedestrians, but these approaches are slower and require stationary cameras to function. The method we present in this work does not require a color difference or constant motion to operate. We use Lucas-Kanade features to track feature points between left and right images, producing a sparse disparity map which is then segmented through the application of k-means clustering. We apply a Viola-Jones face detector to determine which, if any, of the resulting feature clusters represent a trackable person. This algorithm is tested using two identical standard cameras mounted on a mobile robot platform. Results are presented demonstrating detection and tracking of a person in several different situations, including partial occlusion and self-occlusion

Figure-Ground Segmentation Using Multiple Cues

The theme of this thesis is figure-ground segmentation. We address the problem in the context of a visual observer, e.g. a mobile robot, moving around in the world and capable of shifting its gaze to and fixating on objects in its environment. We are only considering bottom-up processes, how the system can detect and segment out objects because they stand out from their immediate background in some feature dimension. Since that implies that the distinguishing cues can not be predicted, but depend on the scene, the system must rely on multiple cues. The integrated use of multiple cues forms a major theme of the thesis. In particular, we note that an observer in our real environment has access to 3-D cues. Inspired by psychophysical findings about human vision we try to demonstrate their effectiveness in figure-ground segmentation and grouping also in machine vision

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 359)

This bibliography lists 164 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Jan. 1992. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

Machine Vision System to Induct Binocular Wide-Angle Foveated Information into Both the Human and Computers - Feature Generation Algorithm based on DFT for Binocular Fixation

This paper introduces a machine vision system, which is suitable for cooperative works between the human and computer. This system provides images inputted from a stereo camera head not only to the processor but also to the user’s sight as binocular wide-angle foveated (WAF) information, thus it is applicable for Virtual Reality (VR) systems such as tele-existence or training experts. The stereo camera head plays a role to get required input images foveated by special wide-angle optics under camera view direction control and 3D head mount display (HMD) displays fused 3D images to the user. Moreover, an analog video signal processing device much inspired from a structure of the human visual system realizes a unique way to provide WAF information to plural processors and the user. Therefore, this developed vision system is also much expected to be applicable for the human brain and vision research, because the design concept is to mimic the human visual system. Further, an algorithm to generate features using Discrete Fourier Transform (DFT) for binocular fixation in order to provide well-fused 3D images to 3D HMD is proposed. This paper examines influences of applying this algorithm to space variant images such as WAF images, based on experimental results

Sledování chůze s použitím senzoru MS Kinect a robotické platformy

Computer vision is a fast developing field of science. Activity monitoring and analysis belongs to this topic. Our application is focused on gait monitoring and analysis. The novelty of this attitude is in the combination of the MS Kinect v2 sensor for capturing the gait pattern and mobility of such sensor thanks to placing this device on a robotic platform. Crucial part of this project is the hardware solution and autonomous function of this recording set. The designed platform is a six-wheeled robotic platform controlled by a micro controller using the depth information from the Kinect sensor and the distance driven by robot provided by encoders attached to every motor. The following research is devoted to the proposal of methods for a precise and as narrow as possible control of the platform and post processing of records for a features selection and a classification of physical activities and early diagnostics of gait disorders, primarily the Parkinson’s disease.Počítačové vidění je rychle se vyvíjející odvětví vědy, kam patří i monitorování a analýza pohybu. Naše aplikace se zaměřuje na zaznamenávání a analýzu chůze a využívá nový přístup v kombinaci senzoru MS Kinect v2 pro sledování pohybových vzorů a robotické platformy jako nosiče, který umožňuje mobilitu senzoru. Stěžejní částí tohoto projektu je samotné hardwarové řešení a autonomní funkce nahrávání. Navrhnutá platforma je šestikolový podvozek řízený jednočipem s využitím hloubkových dat ze senzoru Kinect a ujeté vzdálenosti, která je získávána z šesti enkodérů upevněných na každém motoru. Následujícím úkolem je nelézt a aplikovat metody pro přesné a co nejkomplexnější řízení platformy. Získané nahrávky budou následně podrobeny analýze fyzické aktivity a použity k včasné diagnostice poruch chůze, primárně způsobených Parkinsonovou nemocí

Elderly Assist Robot

This project aimed to create a robot capable of assisting elderly people with tasks in their everyday lives. The project focused on the design, simulation, and the implementation of a mobile robotic base with an attached robotic arm. The project culminated in a prototype robot capable of performing basic chassis and arm control which can be used as a platform for future development