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This paper proposes a method of vision based pose estimation of randomly piled objects. It is necessary to estimate precise rotation angle of picking objects. However, it is non-trivial task because an object placed in every position makes distorted image far from right position image. We propose a precise pose estimation method of bin picking objects. The landmark feature of a picking object is extracted...
Real-time object detection is crucial for many applications of Unmanned Aerial Vehicles (UAVs) such asreconnaissance and surveillance, search-and-rescue, and infras-tructure inspection. In the last few years, Convolutional NeuralNetworks (CNNs) have emerged as a powerful class of modelsfor recognizing image content, and are widely considered inthe computer vision community to be the de facto standardapproach...
Human can recognize an object just by looking at the environment, this capability is very useful for designing the reference of humanoid robot with the ability of adapting it on its environment. By knowing the field conditions that exist in such environments, robot can understand the obstacles or anything that can be passed. To do that, robot vision needs to have a knowledge to understanding an obstacles...
A method is presented for collecting images of static objects from various directions using a mobile robot equipped with a LIDAR unit and an omni-directional camera. A system using this method collects an image sequence for each object along with its geometric information (3D shape and position). The robot estimates its position while moving and detects static objects by using LIDAR. At each time...
With the advance in the research of mobile robots localization algorithms, the need for natural landmark identification has increased. These mobile platforms should have a similar concept of the environment as humans do, without having everything supervised beforehand. The detection of natural landmarks is challenging because their appearance can be different in shape and designs, as well as suffer...
Due to increasing labor costs, the demand for factory automation (FA) continues to rise. Global demand also exists for industrial robots. Thus, autonomous robots that can perform advanced tasks are required in many scientific and technological fields. Although it is difficult for stand-alone robots to perform such random bin-picking tasks as grasping an arbitrary apple from a pile of them, we can...
In this position paper we propose the use of the Distributional Clauses Particle Filter in conjunction with a model-based 3D object tracking method in monocular camera sequences. We describe the model based object tracking method that is based on contour and edge features for 3D pose relative estimation. We also describe the application of the Distributional Clauses Particle Filter that takes into...
In this paper we present a framework for the estimation of the pose of an object in 3D space: from the detection and subsequent recognition from a 3D point-cloud, to tracking in the 2D camera plane. The detection process proposes a way to remove redundant features, which leads to significant computational savings without affecting identification performance. The tracking process introduces a method...
In this paper we present a vision-based approach to detect multiple persons from a mobile robot in real world scenarios using thermal and depth images. First, human upper-body is detected from thermal image to obtain the bounding box coordinates (BBC). This is used as an initial estimate of the position of a person. Then, depth image is fused with the region of interest obtained from the thermal image...
Recently, autonomous robots have been widely used in the production field. There are several advantages to introducing industrial robots in factories. However, these robots cannot be used in unknown environments because most of them are controlled by sequence controls. Two cameras are used as vision sensors that can recognize the outside environment to solve this problem. In this study, we aim at...
This paper presents the development of a first approach to a vision-based target detection. The ultimate objective of this work is to position an autonomous surface vehicle relative to a target. Experiments in a controlled indoor environment were conducted to test the developed system. The experimental results are analyzed and show that the tracking performances achieve errors in the order of a few...
This paper addresses an agent and high resolution image sonar based underwater vehicle's localization method for underwater docking. A novel concept of AUV docking system is proposed. The agent and the support AUV are connected with a tether. For sensing, the agent uses the optical camera and the AUV uses the image sonar. For the agent's localization, the AUV's image sonar guides the agent, wide range...
This paper presents depth evaluation of object detection for automated assembling robots. Pattern distortion analysis from structured light system figures out an object with the highest depth from its background. An automated assembling robot should priory select and pick an object with the highest depth to reduce physical harm during picking action of the robot arm. Object detection is then combined...
Recent advances in development of low-cost 3D sensors, such as Microsoft Kinect, bring attractive opportunities to robot system integrators. The accuracy provided by such sensors is generally unsatisfactory for many robotic applications, but it may be improved through calibration. This paper presents a calibration case study that is based on the sensor calibration procedure involving only a use of...
We present a robotic vision system that is capable of tracking fast moving objects. We briefly describe the design and construction of the system and concentrate on the biological strategies we have implemented to improve the system's capabilities in terms of speed and accuracy. We have also explored new horizons in the area of artificial intelligence to propose some useful algorithms based on visual...
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 human perception of the external world appears as a natural, immediate and effortless task. It is achieved through a number of “low-level” sensory-motor processes that provide a high-level representation adapted to complex reasoning and decision. Compared to these representations, mobile robots usually provide only low-level obstacle maps that lack such highlevel information. We present a mobile...
This paper considers the deployment problem for mobile visual sensor networks equipped with omni-directional communication capability in a non-convex environment. The performance of the visual sensor is assumed to depend not only on the distance but also on the orientation from the sensor to the target. A gradient-based distributed deployment algorithms is designed to maximize the joint detection...
As we know, a novel adaptive visual servoing strategy has been proposed for the control of robot manipulators with an eye-in-hand configuration, where an adaptive law is used to estimate the unknown parameters determined by the products of the unknown 3D coordinates and the unknown camera parameters. From a practical point of view, in this paper, we propose a novel strategy for the estimation of these...
This work presents a simple marker-based person detection method for a mobile robot that can follow a person in indoor environments. Expensive laser range finders or RFID which can provide very accurate range measurements have been used by several researchers for person detection. Recently, vision based approaches have been popular for person detection within a group of multiple people using stereo...
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