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.

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.

The paper focuses on one of the problems of design of an autonomous reactive system, namely, specification of its behavior with respect to (often unpredictable) changes occurring in the real world. Several "behavior-oriented" languages are briefly presented, and some formal relationships between two of them --- Process Transition Networks and Statecharts --- are given. The goal of this presentation is to address the need for augmenting the "behaviorbased design" paradigm with theoretical tools both adequate for expressing complex behaviors of autonomous reactive systems pursuing high-level goals, and applicable to both analysis and synthesis tasks for such systems. 1 Introduction The problem of designing an autonomous system capable of acting in the real world has been the subject of much attention in recent years. The research has focused on designing systems with the following attributes: ffl reactivity, in order to allow the system to cope with unpredictable changes in the dynamic...

In this paper we present a complete control architecture for a mobile robot which enables it to achieve a set of proposed goals with a high degree of autonomy and to react to the changing environment in real time. Autonomy and robustness are achieved through careful selection and incremental implementation of a set of basic Motor-Behaviors that interpret the sensor readings (sonar, vision and odometric sensors) and actuate the motors. The plan is provided by a user, and is expressed as a sequence of goals and a series of hints on how to achieve them. These hints are based on the user's knowledge of the environment and of the robot's behavioral and perceptual abilities. A new set of behaviors, called Conductor-Behaviors, which inspect and modify Motor-Behaviors' attributes, have been introduced in order to link the robot's Motor-Behaviors to the user's plan. Finally, a canonical set of symbols, attached to the Motor-Behaviors, serves as well grounded symbols that the user can utilize to...