Engineering and Computer Science at M.I.T. and a member of the Artificial Intelligence Laboratory where he leads the mobile robot group. He has authored two books, numerous scientific papers, and is the editor of the International Journal of Computer Vision. There is an alternative route to Artificial Intelligence that diverges from the directions pursued under that banner for the last thirty some years. The traditional approach has emphasized the abstract manipulation of symbols, whose grounding, in physical reality has. rarely been achieved. We explore a research methodology which emphasizes ongoing physical interaction with the environment as the primary source of constraint on the design of intelligent systems. We show how this methodology has recently had significant successes on a par with the most successful classical efforts. We outline plausible future work along these lines which can lead to vastly more ambitious systems. 1.

Omnidirectional vision sensors, which have been proposed in 1970, are recently studied in Computer Vision and Multimedia research. This paper discusses features of previously developed omnidirectional vision sensors and their problems in the design. Further, this paper proposes designs of low-cost and compact omnidirectional vision sensors and their new applications. The author considers utilization of omnidirectional vision sensor will be a key issue in Computer Vision and Multimedia applications. Keywords: Omnidirectional vision sensor, Omnidirectional Image, Visual surveillance, Multimedia, Robot vision. 1 Introduction Physical agents living in complex environments, such as humans and animals, need two types of visual sensing abilities. One is to gaze particular objects with a precise but small retina, the other is to look around the environment with a wide but coarse retina. Both visual sensing mechanisms are required for realizing robust and flexible visual behaviors. Especiall...

Complex systems and complex missions take years of planning and force launches to become incredibly expensive. The longer the planning and the more expensive the mission, the more catastrophic if it fails. The solution has always been to plan better, add redundancy, test thoroughly and use high quality components. Based on our experience in building ground based mobile robots (legged and wheeled) we argue here for cheap, fast missions using large numbers of mass produced simple autonomous robots that are small by today's standards (1 to 2 Kg). We argue that the time between mission conception and implementation can be radically reduced, that launch mass can be slashed, that totally autonomous robots can be more reliable than ground controlled robots, and that large numbers of robots can change the tradeoff between reliability of individual components and overall mission success. Lastly, we suggest that within a few years it will be possible at modest cost to invade a planet with millions of tiny robots. 1.

Indoor environments typically consist of sets of connected room-like spaces. We present a local technique that uses range data to detect these spaces during navigation. Our technique includes two parts: segmentation, which isolates room-like spaces and detects when the robot has entered a new one; and feature extraction, which associates each space with a set of geometric features useful for navigation or recognition. Many such features can be considered: here we propose a new method to compute width and length of a rectangular room in a way which is largely invariant with respect to the conguration of the furniture. We report experimental results that show the performance of our technique, and hint at a possible use of this technique for coarse localization on a topological map. 1

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We propose two methods for visual control of a robotic system which do not require the formulation of an explicit calibration between image space and the world coordinate system. Calibration is known to be a difficult and error prone process. By extracting control information directly from the image, we free our techniques from the errors normally associated with a fixed calibration. The two algorithms we propose both utilize feedback from a simple geometric effect, rotational invariance, to control the positioning servo loop. We attach a camera system to a robot such that the camera system and the robot's gripper rotate simultaneously. We also constrain the camera to lie in a position where it can observe the gripper's rotational axis. As the camera system rotates about the gripper's rotational axis, the circular path traced out by a point-like feature projects to an elliptical path in image space. We gather the projected feature points over part of a rotation (=2 radians) ...

We describe a robotic system composed of a manipulator and two cameras. We use the vision system to guide the robot hand to a visible target. The camera positions are known only approximately. Our system does not use the details of the kinematics of the manipulator. There is no common frame of reference linking vision system, workspace and robot hand. The stereo vision system gives information in terms of picture coordinates. This information is used to control a three degree of freedom robot manipulator in a straightforward and robust fashion, in terms of lines and points visible in the images. We describe the implementation with which we tested this idea. In a traditional robot vision system, to work out how to move a robot to manipulate an object, the location of that object must be found in terms of a common reference

through its environment. The robot either explores an unknown environment or navigates through a somewhat familiar environment. The thesis addresses the design of algorithms for 1. environment learning, 2. position estimation using landmarks, 3. visual landmark recognition.

Abstract-In this paper, we present a new designed multi-view single camera and a novel model of scale and illumination invariant corner detection for a service robot in indoor environment. Vision-based simultaneous localization and mapping (VSLAM) has received much attention. It is used for VSLAM that are single cameras, multiple cameras in a stereo setup or omni-directional cameras. We propose a different approach which multiple mirrors are mounted on a vision system in a single-view-point (SVP) configuration. This vision system is easily to acquire no distortion image sequences without any preprocessing. Robust feature detection method is also described for VSLAM of a service robot in indoor environment. This method can detect scale and illumination invariant corner features in any environment. Index Terms—Multi-view single camera, Feature detection, Scale and illumination invariant corner feature (SIICF).

System (GPS) is, de facto, the standard positioning system used in outdoor navigation, it does not provide, per se, all the features required to perform many outdoor navigational tasks. The accuracy of the GPS measurements is the most critical issue. The quest for higher position readings accuracy led to the development, in the late nineties, of the Differential Global Positioning System (DGPS). The differential GPS method detects the range errors of the GPS satellites received and broadcasts them. The DGPS/GPS receivers correlate the DGPS data with the GPS satellite data they are receiving, granting users increased accuracy. DGPS data is broadcasted using terrestrial radio beacons, satellites and, more recently, the Internet. Our goal is to have access, within the ISEP campus, to DGPS correction data. To achieve this objective we designed and implemented a distributed system composed of two main modules which are interconnected: a distributed application responsible for the establishment of the data link over the Internet between the remote DGPS stations and the campus, and the campus-wide DGPS data server application. The DGPS data Internet link is provided by a two-tier client/server distributed