Showing papers on "Mobile robot published in 2000"

Introduction to AI Robotics

Abstract: From the Publisher: This text covers all the material needed to understand the principles behind the AI approach to robotics and to program an artificially intelligent robot for applications involving sensing, navigation, planning, and uncertainty. Robin Murphy is extremely effective at combining theoretical and practical rigor with a light narrative touch. In the overview, for example, she touches upon anthropomorphic robots from classic films and science fiction stories before delving into the nuts and bolts of organizing intelligence in robots. Following the overview, Murphy contrasts AI and engineering approaches and discusses what she calls the three paradigms of AI robotics: hierarchical, reactive, and hybrid deliberative/reactive. Later chapters explore multiagent scenarios, navigation and path-planning for mobile robots, and the basics of computer vision and range sensing. Each chapter includes objectives, review questions, and exercises. Many chapters contain one or more case studies showing how the concepts were implemented on real robots. Murphy, who is well known for her classroom teaching, conveys the intellectual adventure of mastering complex theoretical and technical material.

Collaborative multi-robot exploration

Abstract: In this paper we consider the problem of exploring an unknown environment by a team of robots. As in single-robot exploration the goal is to minimize the overall exploration time. The key problem to be solved therefore is to choose appropriate target points for the individual robots so that they simultaneously explore different regions of their environment. We present a probabilistic approach for the coordination of multiple robots which, in contrast to previous approaches, simultaneously takes into account the costs of reaching a target point and the utility of target points. The utility of target points is given by the size of the unexplored area that a robot can cover with its sensors upon reaching a target position. Whenever a target point is assigned to a specific robot, the utility of the unexplored area visible from this target position is reduced for the other robots. This way, a team of multiple robots assigns different target points to the individual robots. The technique has been implemented and tested extensively in real-world experiments and simulation runs. The results given in this paper demonstrate that our coordination technique significantly reduces the exploration time compared to previous approaches.

A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping

Abstract: We present an incremental method for concurrent mapping and localization for mobile robots equipped with 2D laser range finders. The approach uses a fast implementation of scan-matching for mapping, paired with a sample-based probabilistic method for localization. Compact 3D maps are generated using a multi-resolution approach adopted from the computer graphics literature, fed by data from a dual laser system. Our approach builds 3D maps of large, cyclic environments in real-time, and it is robust. Experimental results illustrate that accurate maps of large, cyclic environments can be generated even in the absence of any odometric data.

A Probabilistic Approach to Collaborative Multi-Robot Localization

Abstract: This paper presents a statistical algorithm for collaborative mobile robot localization. Our approach uses a sample-based version of Markov localization, capable of localizing mobile robots in an any-time fashion. When teams of robots localize themselves in the same environment, probabilistic methods are employed to synchronize each robot's belief whenever one robot detects another. As a result, the robots localize themselves faster, maintain higher accuracy, and high-cost sensors are amortized across multiple robot platforms. The technique has been implemented and tested using two mobile robots equipped with cameras and laser range-finders for detecting other robots. The results, obtained with the real robots and in series of simulation runs, illustrate drastic improvements in localization speed and accuracy when compared to conventional single-robot localization. A further experiment demonstrates that under certain conditions, successful localization is only possible if teams of heterogeneous robots collaborate during localization.

New potential functions for mobile robot path planning

Abstract: The paper first describes the problem of goals unreachable with obstacles nearby when using potential field methods for mobile robot path planning. Then, new repulsive potential functions are presented by taking the relative distance between the robot and the goal into consideration, which ensures that the goal position is the global minimum of the total potential.

Adaptive tracking control of a nonholonomic mobile robot

Abstract: A mobile robot is one of the well-known nonholonomic systems. The integration of a kinematic controller and a torque controller for the dynamic model of a nonholonomic mobile robot has been presented (Fierro and Lewis, 1995). In this paper, an adaptive extension of the controller is proposed. If an adaptive tracking controller for the kinematic model with unknown parameters exists, an adaptive tracking controller for the dynamic model with unknown parameters can be designed by using an adaptive backstepping approach. A design example for a mobile robot with two actuated wheels is provided. In this design, a new kinematic adaptive controller is proposed, then a torque adaptive controller is derived by using the kinematic controller.

PolyBot: a modular reconfigurable robot

Abstract: Modular, self-reconfigurable robots show the promise of great versatility, robustness and low cost. The paper presents examples and issues in realizing those promises. PolyBot is a modular, self-reconfigurable system that is being used to explore the hardware reality of a robot with a large number of interchangeable modules. PolyBot has demonstrated the versatility promise, by implementing locomotion over a variety of terrain and manipulation versatility with a variety of objects. PolyBot is the first robot to demonstrate sequentially two topologically distinct locomotion modes by self-reconfiguration. PolyBot has raised issues regarding software scalability and hardware dependency and as the design evolves the issues of low cost and robustness will be resolved while exploring the potential of modular, self-reconfigurable robots.

Computational principles of mobile robotics

Abstract: Mobile robotics is a multidisciplinary field involving both computer science and engineering. Addressing the design of automated systems, it lies at the intersection of artificial intelligence, computational vision, and robotics. This textbook for advanced undergraduates and graduate students emphasizes algorithms for a range of strategies for locomotion, sensing, and reasoning. It concentrates on wheeled and legged mobile robots but discusses a variety of other propulsion systems. The new edition includes advances in robotics and intelligent machines over the last ten years, including significant coverage of SLAM (simultaneous localization and mapping) and multi-robot systems. It includes additional mathematical background and an extensive list of sample problems. Various mathematical techniques that were assumed in the first edition are now briefly introduced in appendices at the end of the text to make the book more self-contained. Researchers as well as students in the field of mobile robotics will appreciate this comprehensive treatment of state-of-the-art methods and key technologies.

Fom Local Actions to Global Tasks: Stigmergy and Collective Robotics

Abstract: This paper presents a series of experiments where a group of mobile robots gather 81 randomly distributed objects and cluster them into one pile. Coordination of the agents’ movements is achieved through stigmergy. This principle, originally developed for the description of termite building behaviour, allows indirect communication between agents through sensing and modification of the local environment which determines the agents’ behaviour. The efficiency of the work was measured for groups of one to five robots working together. Group size is a critical factor. The mean time to accomplish the task decreases for one, two, and three robots respectively, then increases again for groups of four and five agents, due to an exponential increase in the number of interactions between robots which are time consuming and may eventually result in the destruction of existing clusters. We compare our results with those reported by Deneubourg et al. (1990) where similar clusters are observed in ant colonies, generated by the probabilistic behaviour of workers.

Using Real-Time Stereo Vision for Mobile Robot Navigation

Abstract: This paper describes a working vision-based mobile robot that navigates and autonomously explores its environment while building occupancy grid maps of the environment. We present a method for reducing stereo vision disparity images to two-dimensional map information. Stereo vision has several attributes that set it apart from other sensors more commonly used for occupancy grid mapping. We discuss these attributes, the errors that some of them create, and how to overcome them. We reduce errors by segmenting disparity images based on continuous disparity surfaces to reject “spikes” caused by stereo mismatches. Stereo vision processing and map updates are done at 5 Hz and the robot moves at speeds of 300 cm/s.

Home cleaning robot

Abstract: The present invention is directed to autonomous, microprocessor controlled home cleaning robots having useful functions. More specifically, the present invention relates to autonomous, mobile home cleaning robots having low energy cleaning implements.

Social potentials for scalable multi-robot formations

Abstract: Potential function approaches to robot navigation provide an elegant paradigm for expressing multiple constraints and goals in mobile robot navigation problems. As an example, a simple reactive navigation strategy can be generated by combining repulsion from obstacles with attraction to a goal. Advantages of this approach can also be extended to multirobot teams. In this paper we present a new class of potential functions for multiple robots that enables homogeneous large-scale robot teams to arrange themselves in geometric formations while navigating to a goal location through an obstacle field. The approach is inspired by the way molecules "snap" into place as they form crystals; the robots are drawn to particular "attachment sites" positioned with respect to other robots. We refer to these potential functions as "social potentials" because they are constructed with respect to other agents. Initial results, generated in simulation, illustrate the viability of the approach.

A Gesture Based Interface for Human-Robot Interaction

Abstract: Service robotics is currently a highly active research area in robotics, with enormous societal potential. Since service robots directly interact with people, finding “natural” and easy-to-use user interfaces is of fundamental importance. While past work has predominately focussed on issues such as navigation and manipulation, relatively few robotic systems are equipped with flexible user interfaces that permit controlling the robot by “natural” means. This paper describes a gesture interface for the control of a mobile robot equipped with a manipulator. The interface uses a camera to track a person and recognize gestures involving arm motion. A fast, adaptive tracking algorithm enables the robot to track and follow a person reliably through office environments with changing lighting conditions. Two alternative methods for gesture recognition are compared: a template based approach and a neural network approach. Both are combined with the Viterbi algorithm for the recognition of gestures defined through arm motion (in addition to static arm poses). Results are reported in the context of an interactive clean-up task, where a person guides the robot to specific locations that need to be cleaned and instructs the robot to pick up trash.

Vision-based navigation and environmental representations with an omnidirectional camera

Abstract: 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.

Appearance-Based Obstacle Detection with Monocular Color Vision

Abstract: This paper presents a new vision-based obstacle detection method for mobile robots. Each individual image pixel is classified as belonging either to an obstacle or the ground based on its color appearance. The method uses a single passive color camera, performs in real-time, and provides a binary obstacle image at high resolution. The system is easily trained by simply driving the robot through its environment. In the adaptive mode, the system keeps learning the appearance of the ground during operation. The system has been tested successfully in a variety of environments, indoors as well as outdoors.

Dynamics Filter - concept and implementation of online motion Generator for human figures

Abstract: Humanoid robots are required to make a variety of dynamics and even expressive motions in changing environments. However, the conventional methods for generating humanoid motions fail do achieve this requirement since they can only generate quite artificial and predefined motions through rather complicated optimization processes. In this paper, we propose the concept of "dynamics filter" which transforms a physically inconsistent motion into a consistent one, and provide an example of its implementation using feedback control and local optimization. The optimization is based on the equation of motion of constrained kinematic chains, which is derived from our previously proposed method for computing the dynamics of structure-varying kinematic chains. The proposed method can be applied to online motion generator of humanoid robots.

Sensor resetting localization for poorly modelled mobile robots

Abstract: We present a new localization algorithm, called sensor resetting localization, which is an extension of Monte Carlo localization. The algorithm adds sensor based re-sampling to Monte Carlo localization when the robot is lost. Sensor resetting localization (SRL) is robust to modelling errors including unmodelled movements and systematic errors. It can be used in real time on systems with limited computational power. The algorithm has been successfully used on autonomous legged robots in the Sony legged league of the robotic soccer competition RoboCup'99. We present results from the real robots demonstrating the success of the algorithm and results from simulation comparing SRL to Monte Carlo localization.

Autonomous multi-platform robot system

Abstract: An autonomous mobile robot system allocates mapping, localization, planning and control functions to at least one navigator robot and allocates task performance functions to one or more functional robots. The at least one navigator robot maps the work environment, localizes itself and the functional robots within the map, plans the tasks to be performed by the at least one functional robot, and controls and tracks the at least one functional robot during task performance. The at least one navigator robot performs substantially all calculations for mapping, localization, planning and control for both itself and the functional robots. In one implementation, the at least one navigator robot remains stationary while controlling and moving the at least one functional robot in order to simplify localization calculations. In one embodiment, the at least one navigator robot is equipped with sensors and sensor processing hardware required for these tasks, while the at least one functional robot is not equipped with sensors or hardware employed for these purposes.

Evolutionary artificial potential fields and their application in real time robot path planning

Abstract: A new methodology named Evolutionary Artificial Potential Field (EAPF) is proposed for real-time robot path planning. The artificial potential field method is combined with genetic algorithms, to derive optimal potential field functions. The proposed EAPF approach is capable of navigating robot(s) situated among moving obstacles. Potential field functions for obstacles and goal points are also defined. The potential field functions for obstacles contain tunable parameters. The multi-objective evolutionary algorithm (MOEA) is utilized to identify the optimal potential field functions. Fitness functions such as goal-factor, obstacle-factor, smoothness-factor and minimum-pathlength-factor are developed for the MOEA selection criteria. An algorithm named escape-force is introduced to avoid the local minima associated with EAPF. Moving obstacles and moving goal positions were considered to test the robust performance of the proposed methodology. Simulation results show that the proposed methodology is efficient and robust for robot path planning with non-stationary goals and obstacles.

Mobile Robot Localization and Map Building: A Multisensor Fusion Approach

Abstract: From the Publisher: During the last decade, many researchers have dedicated their efforts to constructing revolutionary machines and to providing them with forms of artificial intelligence to perform some of the most hazardous, risky or monotonous tasks historically assigned to human beings Among those machines, mobile robots are undoubtedly at the cutting edge of current research directions A rough classification of mobile robots can be considered: on the one hand, mobile robots oriented to human-made indoor environments; on the other hand, mobile robots oriented to unstructured outdoor environments, which could include flying oriented robots, space-oriented robots and underwater robots The most common motion mechanism for surface mobile robots is the wheel-based mechanism, adapted both to flat surfaces, found in human-made environments, and to rough terrain, found in outdoor environments However, some researchers have reported successful developments with leg-based mobile robots capable of climbing up stairs, although they require further investigation The research work presented here focuses on wheel-based mobile robots that navigate in human-made indoor environments The main problems described throughout this book are: Representation and integration of uncertain geometric information by means of the Symmetries and Perturbations Model (SPmodel) This model combines the use of probability theory to represent the imprecision in the location of a geometric element, and the theory of symmetries to represent the partiality due to characteristics of each type of geometric element A solution to the first location problem, that is, the computation of an estimation for themobile robot location when the vehicle is completely lost in the environment The problem is formulated as a search in an interpretation tree using efficient matching algorithms and geometric constraints to reduce the size of the solution space The book proposes a new probabilistic framework adapted to the problem of simultaneous localization and map building for mobile robots: the Symmetries and Perturbations Map (SPmap) This framework has been experimentally validated by a complete experiment which profited from ground-truth to accurately validate the precision and the appropriateness of the approach The book emphasizes the generality of the solutions proposed to the different problems and their independence with respect to the exteroceptive sensors mounted on the mobile robot Theoretical results are complemented by real experiments, where the use of multisensor-based approaches is highlighted

Recent progress in local and global traversability for planetary rovers

Abstract: Autonomous planetary rovers operating in vast unknown environments must operate efficiently because of size, power and computing limitations. Recently, we have developed a rover capable of efficient obstacle avoidance and path planning. The rover uses binocular stereo vision to sense potentially cluttered outdoor environments. Navigation is performed by a combination of several modules that each "vote" for the next best action for the robot to execute. The key distinction of our system is that it produces globally intelligent behavior with a small computational resource - all processing and decision making are done on a single processor. These algorithms have been tested on our outdoor prototype rover, Bullwinkle, and have recently driven the rover 100 m at a speed of 15 cm/sec. In this paper we report on the extension on the systems that we have previously developed that were necessary to achieve autonomous navigation in this domain.

Current State of the Art in Distributed Autonomous Mobile Robotics

Abstract: As research progresses in distributed robotic systems, more and more aspects of multi-robot systems are being explored. This article surveys the current state of the art in distributed mobile robot systems. Our focus is principally on research that has been demonstrated in physical robot implementations. We have identified eight primary research topics within multi-robot systems — biological inspirations, communication, architectures, localization/mapping/exploration, object transport and manipulation, motion coordination, reconfigurable robots, and learning — and discuss the current state of research in these areas. As we describe each research area, we identify some key open issues in multi-robot team research. We conclude by identifying several additional open research issues in distributed mobile robotic systems.

Control performance in the horizontal plane of a fish robot with mechanical pectoral fins

Abstract: The mechanism of locomotion of aquatic animals can provide us with new insight into the maneuverability and stabilization of underwater robots. This paper focuses on biomimesis in the maneuvering performance of aquatic animals to develop a new device for maneuvering underwater robots. In this paper, guidance and control in the horizontal plane of a fish robot equipped with a pair of two-motor-driven mechanical pectoral fins on both sides of the robot in water currents is presented. The fish robot demonstrates high performance in terms of maneuverability in such activities as lateral swimming. The use of fuzzy control enables the fish robot to perform rendezvous and docking with an underwater post in water currents.

Design of the TUAT/Karlsruhe humanoid hand

Abstract: The increasing demand for robotic applications in dynamic unstructured environments is motivating the need for dextrous end-effectors which can cope with the wide variety of tasks and objects encountered in these environments. The human hand is a very complex grasping tool that can handle objects of different sizes and shapes. Many research activities have been carried out to develop artificial robot hands with capabilities similar to the human hand. In this paper the mechanism and design of a new humanoid-type hand (called TUAT/Karlsruhe Humanoid Hand) with human-like manipulation abilities is discussed. The new hand is designed for the humanoid robot ARMAR which has to work autonomously or interactively in cooperation with humans and for an artificial lightweight arm for handicapped persons. The arm is developed as close as possible to the human arm and is driven by spherical ultrasonic motors. The ideal end-effector for such an artificial arm or a humanoid would be able to use the tools and objects that a person uses when working in the same environment. Therefore a new hand is designed for anatomical consistency with the human hand. This includes the number of fingers and the placement and motion of the thumb, the proportions of the link lengths and the shape of the palm. It can also perform most part of human grasping types. The TUAT/Karlsruhe Humanoid Hand possesses 20 DOF and is driven by one actuator which can be placed into or around the hand.

Spherical rolling robot: a design and motion planning studies

Abstract: Describes a prototype and analytical studies of a spherical rolling robot, a new design of a nonholonomic robot system. The spherical robot is driven by two remotely controlled, internally mounted rotors that induce the ball to roll and spin on a flat surface. It is tracked on the plane by an overhead camera. A mathematical model of the robot's motion was developed using the nonholonomic constraints on its motion. For a number of simple motions, it is shown experimentally that the model agrees well with the results. Methods were developed for planning feasible, minimum time and minimum energy trajectories for the robot. These methods are illustrated both by mathematical simulation and hardware experiments.

CONRO: Towards Deployable Robots with Inter-Robots Metamorphic Capabilities

Abstract: Metamorphic robots are modular robots that can reconfigure their shape. Such capability is desirable in tasks such as earthquake search and rescue and battlefield surveillance and scouting, where robots must go through unexpected situations and obstacles and perform tasks that are difficult for fixed-shape robots. The capabilities of the robots are determined by the design specification of their modules. In this paper, we present the design specification of a CONRO module, a small, self-sufficient and relatively homogeneous module that can be connected to other modules to form complex robots. These robots have not only the capability of changing their shape (intra-robot metamorphing) but also can split into smaller robots or merge with other robots to create a single larger robot (inter-robot metamorphing), i.e., CONRO robots can alter their shape and their size. Thus, heterogeneous robot teams can be built with homogeneous components. Furthermore, the CONRO robots can separate the reconfiguration stage from the locomotion stage, allowing the selection of configuration-dependent gaits. The locomotion and automatic inter-module docking capabilities of such robots were tested using tethered prototypes that can be reconfigured manually. We conclude the paper discussing the future work needed to fully realize the construction of these robots.

Probabilistic self-localization for mobile robots

Abstract: We describe probabilistic self-localization techniques for mobile robots that are based on the principle of maximum-likelihood estimation. The basic method is to compare a map generated at the current robot position with a previously generated map of the environment in order to probabilistically maximize the agreement between the maps. This method is able to operate in both indoor and outdoor environments using either discrete features or an occupancy grid to represent the world map. The map may be generated using any method to detect features in the robot's surroundings, including vision, sonar, and laser range-finder. We perform an efficient global search of the pose space that guarantees that the best position is found according to the probabilistic map agreement measure in a discretized pose space. In addition, subpixel localization and uncertainty estimation are performed by fitting the likelihood function with a parameterized surface. We describe the application of these techniques in several experiments.