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Visual odometry is a new navigation technology using video data. For long-range navigation, an intrinsic problem of visual odometry is the appearance of drift. The drift is caused by error accumulation, as visual odometry is based on relative measurements, and will grow unboundedly with time. The paper first reviews algorithms which adopt various methods to suppress this drift. However, as far as...
We describe a system which follows “trails” for autonomous outdoor robot navigation. Through a combination of visual cues provided by stereo omnidirectional color cameras and ladar-based structural information, the algorithm is able to detect and track rough paths despite widely varying tread material, border vegetation, and illumination conditions. The approaching trail region is simply modeled as...
Animals and insects use their own navigating system to return home in various ways. One of the most widely used senses is vision. They use visual information to remember the home snapshot image which is useful in returning home from an arbitrary location. Inspired by behaviours of insects and other animals, there have been many homing algorithms applied to mobile robots. These methods use visual information...
Visual maps of the seafloor should ideally provide the ability to measure individual features of interest in real units. Two-dimensional photomosaics cannot provide this capability without making assumptions that often fail over 3-D terrain, and are generally used for visualization, but not for measurement. Full 3-D structure can be recovered using stereo vision, structure from motion (SFM), or simultaneous...
This paper addresses the problem of AUV navigation by showing the feasibility of a stereo visual-inertial approach to odometry retrieval for an AUV. This information is intended as input for a complete SLAM system. After its classification among many other similar approaches in recent work is shown, the algorithm is described in detail. A number of experiments conducted on synthetic data show the...
Differential-drive mobile robots are usually equipped with video-cameras for navigation purposes. In order to ensure proper operational capabilities of such systems, several calibration steps are required to estimate the following quantities: the video-camera intrinsic and extrinsic parameters, the relative pose between the camera and the vehicle frame and, finally, the odometric parameters of the...
The research presented introduces a new methodology to infer environment structure and robot localization by using a monocular machine vision system. The local field of view is constrained to the vicinity of the mobile robot in order to accomplish with robust navigation issues. The strategy proposed uses optical flow techniques and planar models to obtain qualitative 3D information and robot localization...
The use of Autonomous Underwater Vehicles (AUVs) for underwater tasks is a promising robotic field. These robots can carry visual inspection cameras. Besides serving the activities of inspection and mapping, the captured images can also be used to aid navigation and localization of the robots. Visual odometry is the process of determining the position and orientation of a robot by analyzing the associated...
The goal of the autonomous city explorer (ACE) is to navigate autonomously, efficiently and safely in an unpredictable and unstructured urban environment. To achieve this aim, an accurate localization is one of the preconditions. Due to the characteristics of our navigation environment, an elaborated visual odometry system is proposed to estimate the current position and orientation of the ACE platform...
A navigation algorithm for mobile robots in unknown rough terrain has been developed. The algorithm is solely based on stereo images and suitable for wheeled and legged robots. The navigation system is able to guide the robot along a short and safe path to a goal specified by the operator and given in coordinates relative to the starting point of the robot. The algorithm uses visual odometry for localization...
Based on the study of developments in many fields of computer vision, a new approach of computer vision navigation for mobile tracking robot is presented in this paper. The main steps of this approach include object recognition, distance estimation and motion capture. Although these technologies adopted seem to be irrelevant, the combination of them is effective. Interesting observations on distance...
In this research, we propose a unique multi-planar LIDAR and computer vision calibration algorithm. This method only requires the camera and LIDAR to observe a planar pattern at different positions and orientations. Geometric constraints of the dasiaviewspsila from the LIDAR and camera images are resolved as the coordinate transformation coefficients. The proposed approach consists of two stages:...
We present a system that combines multiple visual navigation techniques to achieve GPS-denied, non-line-of-sight SLAM capability for heterogeneous platforms. Our approach builds on several layers of vision algorithms, including sparse frame-to-frame structure from motion (visual odometry), a Kalman filter for fusion with inertial measurement unit (IMU) data and a distributed visual landmark matching...
In the autonomous city explorer (ACE) project a mobile robot is developed, which is capable of finding its way to a given destination in an unknown urban environment. An exemplary mission is to find the way from our institute to the Marienplatz, a public place in the center of Munich, without any prior knowledge or GPS information. Inspired by the behavior of humans in unknown environments, ACE must...
An autonomous robot finds applications in process industries to perform control operations such as manipulation of valves, especially in hazardous environments. This would require localization and mapping capabilities for efficient navigation, coupled with a dexterous arm for manipulation of the valves. Dynamic path planning and obstacle avoidance are the necessary requirements for autonomous navigation...
This paper describes a an SLAM algorithm for the navigation for an indoor autonomous mobile robot. The main emphasis of this paper is on the ability of line extraction. A recognition method based on straight line extraction is proposed for extracting the key features on the office ceiling, in an effort to estimate the pose of mobile robot. Random sample consensus (RANSAC) paradigm is used to group...
This paper reports one experiment conducted to evaluate the influence of oscillating camera motions on the perception of traveled distances in virtual environments. In the experiment, participants viewed visual projections of translations along straight paths. They were then asked to reproduce the traveled distance during a navigation phase using keyboard keys. Each participant had to complete the...
While most mobile robots possess the ability to navigate to and from given locations, for a robot to truly perform guidance, human awareness is also needed. Our guidance robot system possesses both, using a wireless sensor network for navigation and a vision-based tracking system for human awareness. We use the network to create a virtual directional field for the robot. As the network is ad-hoc and...
Personalized localization, navigation and navigation assistance are key issues for almost all aspects of future mobility. We use therefore the SegIT transporter, a new mobile platform based on a Segway Personal Transporter. It is equipped with an onboard video, time-of-flight image and navigation data processing system providing safety and comfort assistance during indoor and outdoor usage. The SegIT...
This paper tackles the problem of vehicle's geo-localisation in urban areas. For this purpose, global positioning system (GPS) receiver is the main sensor. But the use of GPS alone is not sufficient in many urban environments. GPS has so to be helped with dead-reckoned sensors, map data, cameras, range finder ... In this paper, we propose a novel approach to compute observation of the absolute pose...
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