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

Conventional video cameras have limited fields of view which make them restrictive for certain applications in computational vision. A catadioptric sensor uses a combination of lenses and mirrors placed in a carefully arranged configuration to capture a much wider field of view. One important design goal for catadioptric sensors is choosing the shapes of the mirrors in a way that ensures that the complete catadioptric system has a single effective viewpoint. The reason a single viewpoint is so desirable is that it is a requirement for the generation of pure perspective images from the sensed images. In this paper, we derive the complete class of single-lens single-mirror catadioptric sensors that have a single viewpoint. We describe all of the solutions in detail, including the degenerate ones, with reference to many of the catadioptric systems that have been proposed in the literature. In addition, we derive a simple expression for the spatial resolution of a catadioptric sensor in terms of the resolution of the cameras used to construct it. Moreover, we include detailed analysis of the defocus blur caused by the use of a curved mirror in a catadioptric sensor.

A Theory of Single-Viewpoint Catadioptric Image Formation

Catadioptric sensors are devices which utilize mirrors and lenses to form a projection onto the image plane of a camera. Central catadioptric sensors are the class of these devices having a single effective viewpoint. In this paper, we propose a unifying model for the projective geometry induced by these devices and we study its properties as well as its practical implications. We show that a central catadioptric projection is equivalent to a two-step mapping via the sphere. The second step is equivalent to a stereographic projection in the case of parabolic mirrors. Conventional lens-based perspective cameras are also central catadioptric devices with a virtual planar mirror and are, thus, covered by the unifying model. We prove that for each catadioptric projection there exists a dual catadioptric projection based on the duality between points and line images (conics). It turns out that planar and parabolic mirrors build a dual catadioptric projection pair. As a practical example we describe a procedure to estimate focal length and image center from a single view of lines in arbitrary position for a parabolic catadioptric system.

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Catadioptric Projective Geometry

Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges

Proposes a method for the visual-based navigation of a mobile robot in indoor environments, using a single omnidirectional (catadioptric) camera. The geometry of the catadioptric sensor and the method used to obtain a bird's eye (orthographic) view of the ground plane are presented. This representation significantly simplifies the solution to navigation problems, by eliminating any perspective effects. The nature of each navigation task is taken into account when designing the required navigation skills and environmental representations. We propose two main navigation modalities: topological navigation and visual path following. Topological navigation is used for traveling long distances and does not require knowledge of the exact position of the robot but rather, a qualitative position on the topological map. The navigation process combines appearance based methods and visual servoing upon some environmental features. Visual path following is required for local, very precise navigation, e.g., door traversal, docking. The robot is controlled to follow a prespecified path accurately, by tracking visual landmarks in bird's eye views of the ground plane. By clearly separating the nature of these navigation tasks, a simple and yet powerful navigation system is obtained.

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Vision-based navigation and environmental representations with an omnidirectional camera

We designed a new omnidirectional image sensor COPIS (Conic Projection Image Sensor) to guide the navigation of a mobile robot. The feature of COPIS is passive sensing of the omnidirectional image of the environment, in real-time (at the frame rate of a TV camera), using a conic mirror. COPIS is a suitable sensor for visual navigation in a real world environment. We report here a method for navigating a robot by detecting the azimuth of each object in the omnidirectional image. The azimuth is matched with the given environmental map. The robot can precisely estimate its own location and motion (the velocity of the robot) because COPIS observes a 360/spl deg/ view around the robot, even when all edges are not extracted correctly from the omnidirectional image. The robot can avoid colliding against unknown obstacles and estimate locations by detecting azimuth changes, while moving about in the environment. Under the assumption of the known motion of the robot, an environmental map of an indoor scene is generated by monitoring azimuth change in the image. >

Map-based navigation for a mobile robot with omnidirectional image sensor COPIS

Described here is an image sensor with a hyperboloidal mirror for vision based navigation of a mobile robot. Its name is HyperOmni Vision. This sensing system can acquire an omnidirectional view around the robot, in real-time, with use of a hyperboloidal mirror. The authors show a prototype of a mobile robot system with HyperOmni Vision and a method for estimating the motion of the robot and finding unknown obstacles.

Obstacle detection with omnidirectional image sensor HyperOmni Vision

Proposes an efficient and simple method for finding a collision-free path and orientation for a rigid robot in a dynamic observable 3-D environment for unmanned aerial vehicles (UAVs). The method uses an octree for representing every object (robot and static/dynamic obstacles) in the environment without any distinction of the movability of objects; therefore, all objects are dealt with in the same way. The path of a robot from its starting position to the given goal with arbitrary motion (i.e., translation and rotation) in a 3-D environment is efficiently searched for in successive adjoining regions (octree white cells) by using the potential field generated from each black cell of the octree. The algorithm is simple, so it can easily be accelerated by using parallelization techniques. Experimental results obtained under several conditions, such as a point shaped robot and arbitrarily shaped robots in static/dynamic environments, are reported.

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3-D path planning in a dynamic environment using an octree and an artificial potential field

Described here is a method for estimating a rolling motion of a mobile robot from optical flows. We have proposed an image sensor with a hyperboloidal mirror for vision based navigation of the mobile robot. Its name is HyperOmniVision. This sensing system can acquire an omnidirectional view around the robot, in real-time, with use of the hyperboloidal mirror. The radial component of optical flow in HyperOmniVision has a periodic characteristic. The proposed method makes use of this characteristic to estimate robustly the rolling motion of the robot.

Rolling motion estimation for mobile robot by using omnidirectional image sensor HyperOmniVision

Described here is a method for estimating rolling and swaying motions of a mobile robot from optical flows. We have proposed an image sensor with a hyperboloidal mirror for vision based navigation of the mobile robot. Its name is HyperOmni Vision. This sensing system can acquire an omnidirectional view around the robot, in real-time, with use of the hyperboloidal mirror. The radial component of optical flow in HyperOmniVision has a periodic characteristic. The circumferential component of optical flow has a symmetric characteristic. The proposed method makes use of these characteristics to estimate robustly the rolling and swaying motions of the robot.

M. Yachida

Papers

Map-based navigation for a mobile robot with omnidirectional image sensor COPIS

Obstacle detection with omnidirectional image sensor HyperOmni Vision

3-D path planning in a dynamic environment using an octree and an artificial potential field

Rolling motion estimation for mobile robot by using omnidirectional image sensor HyperOmniVision

Stabilization for mobile robot by using omnidirectional optical flow