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This work presents and evaluates the PixelLaser system, designed to estimate range-to-obstacle scans from single images. Its visual pipeline uses nearest-neighbor texture-matching to segment groundplane (traversable) texture from non-groundplane (obstacle) texture. Using the known pose of a webcamera, the system then transforms these segmentations into range-scans. This paper presents a thorough evaluation...
The capability to visually discern possible obstacles from the sky would be a valuable asset to a UAV for avoiding both other flying vehicles and static obstacles in its environment. The main contribution of this article is the presentation of a feasible approach to obstacle avoidance based on the segmentation of camera images into sky and non-sky regions. The approach is named the Sky Segmentation...
A visual cue is introduced that exploits the visual appearance of a single image to estimate the proximity to an obstacle. In particular, the appearance variation cue captures the variation in texture and / or color in the image, and is based on the assumption that there is less such variation when the camera is close to an obstacle. Random sampling is applied in order to evaluate the appearance variation...
This paper presents a method of binocular vision obstacle detection based on SIFT feature matching algorithm. First, a model of depth measurement based on stereo vision is built, it does not require resume the three-dimensional coordinate of spatial point under the world coordinate system. According to the characteristics of the model, we proposed the binocular stereo vision calibration method based...
In this paper, an overview of stereo vision, stereo image processing is introduced as well as a method of obstacle avoidance and navigation based on stereo vision for mobile robot is provided. Making use of 3-d stereo reconstruction, the recognition of visible terrain in front of the mobile robot is solved for successive obstacle avoidance. The area-based stereo reconstruction algorithm which combines...
Sense and avoid systems for civilian unmanned air vehicles (UAVs) are essential in controlled airspace under visual flight rules (VFR). A prototype optical sensor accomplishes the task with attractive performance specifications. Key requirements include long-range detection (up to 10 km), wide field of view, discrimination of small threats against the background and tolerance of direct solar illumination...
This paper provides an intuitive way to inference the space of a scene using stereo cameras. We first segmented the ground out of the image by adaptively learning the ground model in the image. We then used the convex hull to approximate the scene space. Objects within the scene can also be detected with the stereo cameras. Finally, we organized the scene space and the objects within the scene into...
We present a novel method for image-based floor detection from a single image. In contrast with previous approaches that rely upon homographies, our approach does not require multiple images (either stereo or optical flow). It also does not require the camera to be calibrated, even for lens distortion. The technique combines three visual cues for evaluating the likelihood of horizontal intensity edge...
The developed mobile manipulator is primarily composed of a mobile base, a robot manipulator and an eye-in-hand vision system. The material handling of a mobile manipulator has two stages: guiding the mobile base between stations, and picking up a workpiece from a station. Fast landmark recognition and obstacle detection based on color segmentation are proposed for path following, obstacle avoidance...
Detection of obstacles on a plane is important for a mobile robot that moves in a living space, especially for a humanoid that falls down even with a small obstacle. In this paper, a range image sensor for detecting small obstacles on a plane is constructed using a multi-slit laser projector. The sensor consists of a commercially available laser projector and a CCD camera. It measures a relative disparity...
This paper describes a novel approach for purely vision based mobile robot navigation. The visual obstacle avoidance and corridor following behavior rely on the segmentation of the traversable floor region in the omnidirectional robocentric view. The image processing employs a supervised approach in which the segmentation optimal with respect to the appearance of the local environment is determined...
Occupancy grids have been used for a variety of applications in the field of robotics. These grids have typically been created based on data provided by range sensors such as laser or ultrasound. Current practice is to create the grids based on a probabilistic sensor model such as [1]. The use of stereovision to create occupancy grids is less common. This paper will detail a novel approach to compute...
One of the main challenges for autonomous navigation in cluttered outdoor environments is to determine which obstacles can be driven over and which need to be avoided. Especially in off-road driving, the aim is not only to recognize the lethal obstacles on the vehicle's way at all costs, but also to predict the scene category thereby giving a better decision-making framework for vehicle navigation...
This paper proposes an obstacle detection system for the purpose of preventing accidents at level crossings. In order to avoid the limits of already proposed technologies, this system uses stereo cameras to detect and localize multiple targets at the level crossing. In a first step, a background subtraction module is performed using the Color Independent Component Analysis (CICA) technique which allows...
Obstacle avoidance is an important task for autonomous navigation. The paper presents a simple vision based obstacle detection and avoidance algorithm for mobile robots. Using a monocular vision system, a depth map is created in which every pixel of the image captured by the robot is classified in one of the two categories- ground or obstacle. A virtual triangular obstacle is then created on the depth...
Pedestrian protection is an important issue for intelligent vehicles. This paper proposes a new approach for predicting the possibility of a collision between a vehicle and a pedestrian. Almost all pedestrian behavior toward vehicles observed in the real world is considered safe. Therefore, pedestrian behavior that deviates from usual pedestrian behavior indicates a possibility where the vehicle must...
Lots of rear end collisions due to driver inattention have been identified as a major automotive safety issue. A short advance warning can reduce the number and severity of the rear end collisions. This paper describes a Forward Collision Warning (FCW) system based on monocular vision, and presents a new vehicle detection method: appearance-based hypothesis generation, template tracking-based hypothesis...
The Contextual Visual Dataspace (CVD) is a real-time representation of an automotive environment that combines automated 3D modeling and semantic labeling of a scene with dynamic object detection using infrastructure cameras. Our automotive active safety concept uses CVD to detect and track dynamic objects of interest, geo-register them into the semantically labeled 3D world space, analyze the paths...
Safe navigation through corridors plays a major role in the autonomous use of Micro Aerial Vehicles (MAVs) in indoor environments. In this paper, we present an approach for wall collision avoidance using a depth map based on optical flow from on board camera images. An omnidirectional fisheye camera is used as a primary sensor, while IMU data is needed for compensating rotational effects of the optical...
This paper presents the solution of stereo correspondence problem occur in comparing stereo images on stereo vision mobile robot using block matching algorithm. The algorithm is using Sum of Absolute Differences (SAD). Left image works as a reference block to the right image and the output is disparity mapping with the left coordinate system. The stereo vision baseline is based on horizontal configuration...
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