The ability to navigate with limited vision is a skill that is often employed in our daily lives. Navigating without vision to a remembered target has previously been studied. However, not much is known about the attention required to perform blind navigation. We examined the effect of aging and presence of obstacles on the attentional demands of blind navigation. We evaluated reaction time, navigation errors and average walking speed in an 8 meter walking path, with or without obstacles, in the absence of vision. Results showed that older participants had increased reaction time and increased linear distance travelled as opposed to young participants, that obstacles increased reaction time and decreased average walking speed in all participants, and that emitting the reaction time stimulus early in the trial increased the linear distance travelled. Interpretation of the results suggests that aging and presence of obstacles augments the attentional demands of blind navigation.

Abstract   Many researchers in social work believe that in today's society require the interaction between organisations takes place on social problems. This study examined the interaction between the police, social services and schools. The purpose of this study are as follows; the aim is to investigate the interaction between social services, the police and schools about young people aged 12-18 years who are at risk for abuse and crime. My questions are: How do the different professions interact regarding young people at risk for abuse and crime? How do they meet young people in their daily work? What obstacles can the different professions see in interaction? What effects do the different professions see in interaction? The study is a qualitative study conducted with semi-structured interviews. Respondents have been two from each organisation. The theory used in the analysis of empirical data is new-institutionalismen. New-institutionalism is a theory developed from organizational theories. Research emanating from organizations influence from the outside world has been designated a new - institutionalism. The new institutionalism is based on individuals, and environmental impact on the organization, as well as their interaction The results of the study mean that different privacy laws are an obstacle in the interaction and also lack of resources is a barrier. This study also shows a positive attitude towards interaction between the different organizations.   Keywords: Interaction, Police, Social service, School, Obstacle, Domain consensus, Domain conflict

Many potential indoor applications exist for autonomous vehicles, such as automated surveillance, inspection, and document delivery. A key requirement for autonomous operation is for the vehicles to be able to detect and map obstacles in order to avoid collisions. This work develops a comprehensive 3D scene reconstruction algorithm based on known vehicle motion and vision data that is specifically tailored to the indoor environment. Visible light cameras are one of the many sensors available for capturing information from the environment, and their key advantages over other sensors are that they are light weight, power efficient, cost effective, and provide abundant information about the scene. The emphasis on 3D indoor mapping enables the assumption that a large majority of the area to be mapped is comprised of planar surfaces such as floors, walls and ceilings, which can be exploited to simplify the complex task of dense reconstruction of the environment from monocular vision data. In this thesis, the Planar Surface Reconstruction (PSR) algorithm is presented. It extracts surface information from images and combines it with 3D point estimates in order to generate a reliable and complete environment map. It was designed to be used for single cameras with the primary assumptions that the objects in the environment are flat, static and chromatically unique. The algorithm finds and tracks Scale Invariant Feature Transform (SIFT) features from a sequence of images to calculate 3D point estimates. The individual surface information is extracted using a combination of the Kuwahara filter and mean shift segmentation, which is then coupled with the 3D point estimates to fit these surfaces in the environment map. The resultant map consists of both surfaces and points that are assumed to represent obstacles in the scene. A ground vehicle platform was developed for the real-time implementation of the algorithm and experiments were done to assess the PSR algorithm. Both clean and cluttered scenarios were used to evaluate the quality of the surfaces generated from the algorithm. The clean scenario satisfies the primary assumptions underlying the PSR algorithm, and as a result produced accurate surface details of the scene, while the cluttered scenario generated lower quality, but still promising, results. The significance behind these findings is that it is shown that incorporating object surface recognition into dense 3D reconstruction can significantly improve the overall quality of the environment map.

The goal of this thesis is to implement the control and design of an intelligent vehicle based on an embedded DSP platform (eZdspTM F2812). The overall system including steering wheel AC serve motor, brake actuator, throttle driving circuit and the sensors is equipped in a golf car as a platform. Otherwise, digital image processing technology is used to realize the autonomous driving system which can achieve multi-mode of lane-keeping, lane-change and obstacle-avoidance. In the lane-keeping control, the road information can be provided by the vision system. According to the offset and displacement of angle as input signal, a fuzzy controller is used to compute the desired steering wheel angle and let the golf car can cross road safely. In lane-change, a smooth trajectory can be generated by IMU, IMU is used to collect the information data of yaw rate and yaw angle when human-driving. That makes autonomous driving system become more humanlike and to achieve an open-loop lane-change maneuver. In obstacle-avoidance, we use a laser range scanner to detect the distance of a front obstacle. When the distance is lower than safety distance, double lane-change will be activated to avoid the front obstacle. The overall system has been examined on NSYSU campus roads.

This research plans the power capacities of the obstacle lighting on the power transmission towers, which are located in the areas where the utility cannot reach. The obstacle lighting is formed by light emitting diodes (LEDs), which are powered mainly by solar cells and subordinately by rechargeable batteries. The solar cells charge the batteries during the sunny daytime with plenty sunlight. When the sunlight is insufficient and the obstacle lamp is turned on, batteries and solar cells supply the obstacle lighting simultaneously. The power capacities of the solar cells and batteries are designated to keep the obstacle lighting system uninterruptible either under the drastic weather variation or a long period of insufficient sunlight. Under the specified operation rules of the obstacle lighting, a more economical and precise method is proposed for planning the power capacities of solar cells and batteries based on the weather data from Central Weather Bureau in recent 6 years following. The power planning method is implemented in the areas of Kaohsiung, Chiayi and Ali mountain to demonstrate the feasibility and the accuracy in reality.

In daily life, there are a lot of inconveniences for the vision disabled people, even thought there are few equipments for them to use. However, there has no equipment to guide the vision disabled people on the pedestrian crossing, it will cause them being a dangerous situation while through the pedestrian crossing. To design an intelligent vehicle to help vision disabled people through the pedestrian crossing safely is an important topic. This thesis presents an autonomous transportation robot in intersections to provide older and vision disabled people to through the pedestrian crossing safely. This robot is based on a commercial wheelchair which equipped with cameras, inertial measurement unit, encoder, GPS module, hearts rate sensor, etc. In this study, by using the camera settled in the top of the robot to capture the picture, it could detect the region of pedestrian crossing and find the obstacles and pedestrian on the pedestrian crossing with image processing techniques. Then using the fuzzy controller to do the obstacle avoidance or people following. This robot can make the automatic parking after through the pedestrian crossing and transmit the position of the robot and the user¡¦s heart rate to the remote monitor system.

Thèse de doctorat : TERRE, OCEAN, ESPACE : Nice : 1997. / 1997NICE5144. 69 REF.

In this work we develop optical flow templates. In doing so, we introduce a practical tool for inferring robot egomotion and semantic superpixel labeling using optical flow in imaging systems with arbitrary optics. In order to do this we develop valuable understanding of geometric relationships and mathematical methods that are useful in interpreting optical flow to the robotics and computer vision communities. This work is motivated by what we perceive as directions for advancing the current state of the art in obstacle detection and scene understanding for mobile robots. Specifically, many existing methods build 3D point clouds, which are not directly useful for autonomous navigation and require further processing. Both the step of building the point clouds and the later processing steps are challenging and computationally intensive. Additionally, many current methods require a calibrated camera, which introduces calibration challenges and places limitations on the types of camera optics that may be used. Wide-angle lenses, systems with mirrors, and multiple cameras all require different calibration models and can be difficult or impossible to calibrate at all. Finally, current pixel and superpixel obstacle labeling algorithms typically rely on image appearance. While image appearance is informative, image motion is a direct effect of the scene structure that determines whether a region of the environment is an obstacle. The egomotion estimation and obstacle labeling methods we develop here based on optical flow templates require very little computation per frame and do not require building point clouds. Additionally, they do not require any specific type of camera optics, nor a calibrated camera. Finally, they label obstacles using optical flow alone without image appearance. In this thesis we start with optical flow subspaces for egomotion estimation and detection of “motion anomalies”. We then extend this to multiple subspaces and develop mathematical reasoning to select between them, comprising optical flow templates. Using these we classify environment shapes and label superpixels. Finally, we show how performing all learning and inference directly from image spatio-temporal gradients greatly improves computation time and accuracy.

Abstract not available. / text

In 2003 years the behaviour of ant Lasius fuliginosus was explored. The trial was made in two ways: a) by different sizes of white sheet of paper then the weather conditions were sunny, cloudy, rainy; b) turning one part of path by cant of 180.