Surveys the developments of the last 20 years in the area of vision for mobile robot navigation. Two major components of the paper deal with indoor navigation and outdoor navigation. For each component, we have further subdivided our treatment of the subject on the basis of structured and unstructured environments. For indoor robots in structured environments, we have dealt separately with the cases of geometrical and topological models of space. For unstructured environments, we have discussed the cases of navigation using optical flows, using methods from the appearance-based paradigm, and by recognition of specific objects in the environment.

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Vision for mobile robot navigation: a survey

Mobile robot vision-based navigation has been the source of countless research contributions, from the domains of both vision and control. Vision is becoming more and more common in applications such as localization, automatic map construction, autonomous navigation, path following, inspection, monitoring or risky situation detection. This survey presents those pieces of work, from the nineties until nowadays, which constitute a wide progress in visual navigation techniques for land, aerial and autonomous underwater vehicles. The paper deals with two major approaches: map-based navigation and mapless navigation. Map-based navigation has been in turn subdivided in metric map-based navigation and topological map-based navigation. Our outline to mapless navigation includes reactive techniques based on qualitative characteristics extraction, appearance-based localization, optical flow, features tracking, plane ground detection/tracking, etc... The recent concept of visual sonar has also been revised.

Visual Navigation for Mobile Robots: A Survey

The authors describe a method for locating a mobile robot moving in a known environment. This technique combines position estimation from odometry with observations of the environment from a mobile camera. Fixed objects in the world provide landmarks which are listed in a database. The system calculates the angle to each landmark and then orients the camera. An extended Kalman filter is used to correct the error between the observed and estimated angle to each landmark. Results from experiments in a real environment are presented. >

Position estimation for a mobile robot using vision and odometry

A closed-form analytical solution to the problem of 3D estimation of circular-feature location is presented. Two different cases are considered: 3D orientation and position estimation when the radius is known and when it is not known. Extension of the method to general 3D quadratic features is also addressed. Simulated experimental results obtained for all three cases verified the analytical method. In the case of real experiments, a set of circles located on a calibration plate, whose locations were known with respect to a reference frame, were used for camera calibration as well as for the application of the method. A sequential compensation procedure was applied to the input gray-level image to compensate for distortion. These results also showed the validity of the process and the applicability of the analytical method. >

Three-dimensional location estimation of circular features for machine vision

Pose estimation is an important operation for many vision tasks. In this paper, the authors propose an algorithm for pose estimation based on the volume measurement of tetrahedra composed of feature-point triplets extracted from an arbitrary quadrangular target and the lens center of the vision system. The inputs to this algorithm are the six distances joining all feature pairs and the image coordinates of the quadrangular target. The outputs of this algorithm are the effective focal length of the vision system, the interior orientation parameters of the target, the exterior orientation parameters of the camera with respect to an arbitrary coordinate system if the target coordinates are known in this frame, and the final pose of the camera. The authors have also developed a shape restoration technique which is applied prior to pose recovery in order to reduce the effects of inaccuracies caused by image projection. An evaluation of the method has shown that this pose estimation technique is accurate and robust. Because it is based on a unique and closed form solution, its speed makes it a potential candidate for solving a variety of landmark-based tracking problems. >

A new efficient and direct solution for pose estimation using quadrangular targets: algorithm and evaluation

As mobile robots are taking on more and more of the tasks that were normally delegated to humans, they need to acquire higher degrees of autonomous operation, which calls for accurate and efficient position determination and/or verification The critical geometric dimensions of a standard pattern are used here to locate the relative position of the mobile robot with respect to the pattern; by doing so, the method does not depend on values of any intrinsic camera parameters, except the focal length In addition, this method has the advantages of simplicity and flexibility This standard pattern is also provided with a unique identification code, using bar codes, that enables the system to find the absolute location of the pattern These bar codes also assist in the scanning algorithms to locate the pattern in the environment A thorough error analysis and experimental results obtained through software simulation are presented, as well as the current direction of our work

Position verification of a mobile robot using standard pattern

An image processor used as a position transducer is treated on an input-output basis. If processing speed is sufficiently fast the input-output characteristic is independent of frequency and can be represented as a gain function. The input is a function of the image pattern (including intensity if grey level is used) and the output is used for control or other purposes but control is the issue considered here. A Fourier phase in conjunction with projection concepts is used to obtain control signals in the image processing. A solution to two-dimensional rotation of the object input pattern is presented. The technique can easily be extended to deal with dilation problem. Results that are important to closed loop design are included.

M. Kabuka

Papers

Position verification of a mobile robot using standard pattern

Input-output characteristics for imaged transducers