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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...
Handheld manipulable objects can often be found on flat surfaces within human environments. Researchers have previously demonstrated that perceptually segmenting a flat surface from the objects resting on it can enable robots to pick and place objects. However, methods for performing this segmentation can fail when applied to scenes with natural clutter. For example, low-profile objects and dense...
This paper comes up with the dual Otsu threshold method based on four-color block and K-L transform, which can be used to segment the image and extract the objective as well as identify the objective by the color characteristics. This method realizes real-time adjustment of the image segmentation threshold and improves the accuracy, timeliness and robustness of the visual system. Finally, with the...
Real-time and accurate image matching is a key to stereo vision of agricultural harvesting robots. This research is part of a pineapple harvesting robot project. In this paper, pineapples were selected as research objects and low cost binocular vision platform was constructed, fruit area of left image was got by real-time image acquisition and rapid segmentation, rapid matching of fruit area in left...
This paper presents a novel solution to the autonomy of a Portable Robotic Device (PRD) for the visually impaired. The proposed method meets the PRD's requirement of providing 3D navigational information with a small-sized device. The proposed approach is to employ a 3D imaging sensor-the SwissRanger SR4000-for both pose estimation and perception. The SR4000 produces both intensity and range images...
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...
Autonomous mobile robot navigation is a very relevant problem in robotics research. This paper proposes a vision-based autonomous navigation system using artificial neural networks (ANN) and finite state machines (FSM). In the first step, ANNs are used to process the image frames taken from the robot's camera, classifying the space, resulting in navigable or non-navigable areas (image road segmentation)...
With the research and development of chess robot and machine vision, chess robot with visual function has recently received an increasing interest in the community. This paper introduces the chess system of dual-robot coordination based on vision and the process of visual system structure, gives the coordinates translation from computer and image coordinates to actual coordinates. And in the process...
In this paper we present an approach to object segmentation and recognition that combines depth and color cues. We fuse information from color images with depth from a Time-of-Flight (ToF) camera to improve recognition performance under scale and viewpoint changes. Firstly, we use depth and local surface orientation extracted from the ToF image to normalize color and depth image features with regard...
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...
In this paper, we propose a novel monocular SLAM method in corridor environment which employs Segments-on-Floor (SoF) as feature data. Given that the height of the camera and the angle between the camera and the floor are known, an image of the SoF can be efficiently distinguished from the other space-lines by a simple data-association method, deriving the line correspondence from a simplified homography...
This paper presents a vision-based obstacle avoidance design using a monocular camera onboard a mobile robot. An image processing procedure is developed to estimate distances between the robot and obstacles based-on inverse perspective transformation (IPT) in image plane. A robust image processing solution is proposed to detect and segment navigatable ground plane area within the camera view. The...
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...
We investigate the existence of computationally inexpensive first and second order statistics that uniquely describe grass for application in an autonomous lawnmower. We then segment images based on these statistics to determine locations of driveable terrain in an image. Tight statistical clustering of illuminated grass versus artificial texture suggests that this method is sufficient for identifying...
This article presents a novel object recognition module which is adapted to the needs in mobile service robotics. It uses information provided from a stereo camera system as pre-processing part of SIFT or SURF. The principle idea is to filter irrelevant information by selecting regions of interest in the disparity map from stereo images and to use the geometrical constraints of the stereo camera system...
We propose a method for multi-modal scene exploration where initial object hypothesis formed by active visual segmentation are confirmed and augmented through haptic exploration with a robotic arm. We update the current belief about the state of the map with the detection results and predict yet unknown parts of the map with a Gaussian Process. We show that through the integration of different sensor...
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...
We present an extension of a neuro-dynamic object recognition system that combines bottom-up recognition of matching patterns and top-down estimation of pose parameters in a recurrent loop. It is extended by an active foveal vision system. Adding the active vision component is easily integrated within the architecture and improves the recognition rate on previous experiments on the COIL-100 database...
This work aims to promote integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicles equipped with a camera and a 2D laser range finder. A method to check for inconsistencies between the data provided by these two heterogeneous sensors is proposed and discussed. First, uncertainties in the estimated transformation between the laser and camera frames are evaluated...
This paper describes a novel approach to surface fitting for the creation of a 3D surface map for use by a small articulated wall-climbing robot. Both a laser range finder and a low-resolution camera are used to acquire data in a sparse manner. By scanning at large intervals, such as every 5-10°, and then fusing the data, it is shown that it is possible to fit planar surfaces at an accuracy comparable...
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