Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the “configuration spaces” of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. Developed from courses taught by the author, the book is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.

Planning Algorithms: Introductory Material

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

There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting cooperative behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of cooperative robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.

Cooperative mobile robotics: antecedents and directions

There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting collective behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of collective robotics have been reported, and supporting theory is still in its formative stages. In this paper, the authors give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. The authors describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.

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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 paper proposes basic concepts of cooperation of multiple autonomous mobile robots, The authors suggest to divide the cooperation into two types, active and nonactive according to the setting goal of the system. And in nonactive cooperation there must be 'modest cooperation' to prevent any collision of resource access by the robots. The way to design multiple robots system is also discussed. >

Consideration on the cooperation of multiple autonomous mobile robots

The authors aim at map based outdoor navigation of a mobile robot. In navigation, robot position is fundamentally obtained by odometry. However, the position is misaligned as the robot moves because odometry has cumulative error. DGPS measurement data may cancel its position error. The framework of EKF is used for the modification and the fusion between odometry and DGPS measurement data. The DGPS measurement data, however, could have large error because of multipath near buildings. In this paper, the authors propose a method which eliminates erroneous DGPS measurement data when odometry robot position is fused, and confirm the validity of this approach.

Outdoor navigation of a mobile robot between buildings based on DGPS and odometry data fusion

The problem of organizing a multiple autonomous mobile robot system is considered. At any moment, the behavior of each robot, in a multi robot society, is in one of two phases either; (1)working for its own purpose, or (2)working for a common purpose with one or more other robots. In situation(l), the robot operates under its own decision making using the principle of modest cooperation. In situation(2), each robot does not make its own decisions, instead one robot is selected as a leader and decides the behavior of all the concerned robots. While the multi robot system is functioning, each robot will be switching its decision making mode, between the autonomous and the centralized methods. In this way, the coordinated behaviors of the multiple autonomous robots can be easily designed and achieved .

Coordinating Autonomous And Centralized Decision Making To Achieve Cooperative Behaviors Between Multiple Mobile Robots

Discusses the trajectory control for a wheeled inverse pendulum type mobile robot. The robot considered has two independent driving wheels on the same axle, and a gyro type sensor for measuring the inclination angular velocity of the body and rotary encoders to measure the wheels' rotation. The purpose of the authors' work is to make the robot autonomously navigate in a two dimensional plane while keeping balance of its body. The control algorithm consists of three parts; the balancing and velocity control, the heading control, and the trajectory control part. The authors designed and implemented a vehicle command system for this robot with the proposed algorithm. Experiments in real world navigation have been made by using the authors' experimental system "Yamabico Kurara". >

Trajectory tracking control for navigation of self-contained mobile inverse pendulum

A vehicle command system for the wheeled autonomous mobile robot with a high capability in describing the navigation task in the real environment, is proposed. And a feedback control method to track along the given path by the vehicle commands is described. The effectiveness of the proposed vehicle command system and the trajectory control method are confirmed by numerical simulations and experiments in the real environment using a self-contained autonomous mobile robot. >

S. Yuta

Papers

Consideration on the cooperation of multiple autonomous mobile robots

Outdoor navigation of a mobile robot between buildings based on DGPS and odometry data fusion

Coordinating Autonomous And Centralized Decision Making To Achieve Cooperative Behaviors Between Multiple Mobile Robots

Trajectory tracking control for navigation of self-contained mobile inverse pendulum

Vehicle command system and trajectory control for autonomous mobile robots