Showing papers on "Mobile robot published in 2004"

Introduction to Autonomous Mobile Robots

Abstract: Mobile robots range from the Mars Pathfinder mission's teleoperated Sojourner to the cleaning robots in the Paris Metro. This text offers students and other interested readers an introduction to the fundamentals of mobile robotics, spanning the mechanical, motor, sensory, perceptual, and cognitive layers the field comprises. The text focuses on mobility itself, offering an overview of the mechanisms that allow a mobile robot to move through a real world environment to perform its tasks, including locomotion, sensing, localization, and motion planning. It synthesizes material from such fields as kinematics, control theory, signal analysis, computer vision, information theory, artificial intelligence, and probability theory. The book presents the techniques and technology that enable mobility in a series of interacting modules. Each chapter treats a different aspect of mobility, as the book moves from low-level to high-level details. It covers all aspects of mobile robotics, including software and hardware design considerations, related technologies, and algorithmic techniques.] This second edition has been revised and updated throughout, with 130 pages of new material on such topics as locomotion, perception, localization, and planning and navigation. Problem sets have been added at the end of each chapter. Bringing together all aspects of mobile robotics into one volume, Introduction to Autonomous Mobile Robots can serve as a textbook or a working tool for beginning practitioners.

Cooperative control of mobile sensor networks:Adaptive gradient climbing in a distributed environment

Abstract: We present a stable control strategy for groups of vehicles to move and reconfigure cooperatively in response to a sensed, distributed environment. Each vehicle in the group serves as a mobile sensor and the vehicle network as a mobile and reconfigurable sensor array. Our control strategy decouples, in part, the cooperative management of the network formation from the network maneuvers. The underlying coordination framework uses virtual bodies and artificial potentials. We focus on gradient climbing missions in which the mobile sensor network seeks out local maxima or minima in the environmental field. The network can adapt its configuration in response to the sensed environment in order to optimize its gradient climb.

PID vs LQ control techniques applied to an indoor micro quadrotor

Abstract: The development of miniature flying robots has become a reachable dream, thanks to the new sensing and actuating technologies. Micro VTOL systems represent a useful class of flying robots because of their strong abilities for small-area monitoring and building exploration. In this paper, we present the results of two model-based control techniques applied to an autonomous four-rotor micro helicopter called quadrotor. A classical approach (PID) assumed a simplified dynamics and a modern technique (LQ) based on a more complete model. Various simulations were performed and several tests on the bench validate the control laws. Finally, we present the results of the first test in flight with the helicopter released. These developments are part of the OS4 project in our lab.

Cyberbotics Ltd. Webots™: Professional Mobile Robot Simulation:

Abstract: Cyberbotics Ltd. develops Webots™, a mobile robotics simulation software that provides you with a rapid prototyping environment for modelling, programming and simulating mobile robots. The provided robot libraries enable you to transfer your control programs to several commercially available real mobile robots. Webots™ lets you define and modify a complete mobile robotics setup, even several different robots sharing the same environment. For each object, you can define a number of properties, such as shape, color, texture, mass, friction, etc. You can equip each robot with a large number of available sensors and actuators. You can program these robots using your favorite development environment, simulate them and optionally transfer the resulting programs onto your real robots. Webots™ has been developed in collaboration with the Swiss Federal Institute of Technology in Lausanne, thoroughly tested, well documented and continuously maintained for over 7 years. It is now the main commercial product availabl...

A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots

Abstract: Autonomous mobile robots navigating in changing and dynamic unstructured environments like the outdoor environments need to cope with large amounts of uncertainties that are inherent of natural environments. The traditional type-1 fuzzy logic controller (FLC) using precise type-1 fuzzy sets cannot fully handle such uncertainties. A type-2 FLC using type-2 fuzzy sets can handle such uncertainties to produce a better performance. In this paper, we present a novel reactive control architecture for autonomous mobile robots that is based on type-2 FLC to implement the basic navigation behaviors and the coordination between these behaviors to produce a type-2 hierarchical FLC. In our experiments, we implemented this type-2 architecture in different types of mobile robots navigating in indoor and outdoor unstructured and challenging environments. The type-2-based control system dealt with the uncertainties facing mobile robots in unstructured environments and resulted in a very good performance that outperformed the type-1-based control system while achieving a significant rule reduction compared to the type-1 system.

Design and control of an indoor micro quadrotor

Abstract: Progresses in sensor technology, data processing and integrated actuators has made the development of miniature flying robots fully possible. Micro VTOL systems represent a useful class of flying robots because of their strong capabilities for small-area monitoring and building exploration. In this paper we describe the approach that our lab has taken to micro VTOL evolving towards full autonomy, and present the mechanical design, dynamic modelling, sensing, and control of our indoor VTOL autonomous robot OS4.

Mapping and localization with RFID technology

Abstract: We analyze whether radio frequency identification (RFID) technology can be used to improve the localization of mobile robots and persons in their environment. In particular we study the problem of localizing RFID tags with a mobile platform that is equipped with a pair of RFID antennas. We present a probabilistic measurement model for RFID readers that allow us to accurately localize RFID tags in the environment. We also demonstrate how such maps can be used to localize a robot and persons in their environment. Finally, we present experiments illustrating that the computational requirements for global robot localization can be reduced strongly by fusing RFID information with laser data.

Simultaneous Localization and Mapping with Sparse Extended Information Filters

Abstract: In this paper we describe a scalable algorithm for the simultaneous mapping and localization (SLAM) problem. SLAM is the problem of acquiring a map of a static environment with a mobile robot. The vast majority of SLAM algorithms are based on the extended Kalman filter (EKF). In this paper we advocate an algorithm that relies on the dual of the EKF, the extended information filter (EIF). We show that when represented in the information form, map posteriors are dominated by a small number of links that tie together nearby features in the map. This insight is developed into a sparse variant of the EIF, called the sparse extended information filter (SEIF). SEIFs represent maps by graphical networks of features that are locally interconnected, where links represent relative information between pairs of nearby features, as well as information about the robot’s pose relative to the map. We show that all essential update equations in SEIFs can be executed in constant time, irrespective of the size of the map. We...

Noninvasive brain-actuated control of a mobile robot by human EEG

Abstract: Brain activity recorded noninvasively is sufficient to control a mobile robot if advanced robotics is used in combination with asynchronous electroencephalogram (EEG) analysis and machine learning techniques. Until now brain-actuated control has mainly relied on implanted electrodes, since EEG-based systems have been considered too slow for controlling rapid and complex sequences of movements. We show that two human subjects successfully moved a robot between several rooms by mental control only, using an EEG-based brain-machine interface that recognized three mental states. Mental control was comparable to manual control on the same task with a performance ratio of 0.74.

Policy gradient reinforcement learning for fast quadrupedal locomotion

Abstract: This paper presents a machine learning approach to optimizing a quadrupedal trot gait for forward speed. Given a parameterized walk designed for a specific robot, we propose using a form of policy gradient reinforcement learning to automatically search the set of possible parameters with the goal of finding the fastest possible walk. We implement and test our approach on a commercially available quadrupedal robot platform, namely the Sony Aibo robot. After about three hours of learning, all on the physical robots and with no human intervention other than to change the batteries, the robots achieved a gait faster than any previously known gait known for the Aibo, significantly outperforming a variety of existing hand-coded and learned solutions.

Human-robot interaction in rescue robotics

Abstract: Rescue robotics has been suggested by a recent DARPA/NSF study as an application domain for the research in human-robot integration (HRI). This paper provides a short tutorial on how robots are currently used in urban search and rescue (USAR) and discusses the HRI issues encountered over the past eight years. A domain theory of the search activity is formulated. The domain theory consists of two parts: 1) a workflow model identifying the major tasks, actions, and roles in robot-assisted search (e.g., a workflow model) and 2) a general information flow model of how data from the robot is fused by various team members into information and knowledge. The information flow model also captures the types of situation awareness needed by each agent in the rescue robot system. The article presents a synopsis of the major HRI issues in reducing the number of humans it takes to control a robot, maintaining performance with geographically distributed teams with intermittent communications, and encouraging acceptance within the existing social structure.

Nearness diagram (ND) navigation: collision avoidance in troublesome scenarios

Abstract: This paper addresses the reactive collision avoidance for vehicles that move in very dense, cluttered, and complex scenarios. First, we describe the design of a reactive navigation method that uses a "divide and conquer" strategy based on situations to simplify the difficulty of the navigation. Many techniques could be used to implement this design (since it is described at symbolic level), leading to new reactive methods that must be able to navigate in arduous environments (as the difficulty of the navigation is simplified). We also propose a geometry-based implementation of our design called the nearness diagram navigation. The advantage of this reactive method is to successfully move robots in troublesome scenarios, where other methods present a high degree of difficulty in navigating. We show experimental results on a real vehicle to validate this research, and a discussion about the advantages and limitations of this new approach.

A neural network approach to complete coverage path planning

Abstract: Complete coverage path planning requires the robot path to cover every part of the workspace, which is an essential issue in cleaning robots and many other robotic applications such as vacuum robots, painter robots, land mine detectors, lawn mowers, automated harvesters, and window cleaners. In this paper, a novel neural network approach is proposed for complete coverage path planning with obstacle avoidance of cleaning robots in nonstationary environments. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation derived from Hodgkin and Huxley's (1952) membrane equation. There are only local lateral connections among neurons. The robot path is autonomously generated from the dynamic activity landscape of the neural network and the previous robot location. The proposed model algorithm is computationally simple. Simulation results show that the proposed model is capable of planning collision-free complete coverage robot paths.

Sliding-mode tracking control of nonholonomic wheeled mobile robots in polar coordinates

Abstract: This brief proposes a sliding-mode control method for wheeled-mobile robots in polar coordinates. A new sliding-mode control method is proposed for mobile robots with kinematics in two-dimensional polar coordinates. In the proposed method, two controllers are designed to asymptotically stabilize the tracking errors in position and heading direction, respectively. By combining these controllers together, both asymptotic posture (position and heading direction) stabilization and trajectory tracking are achieved for reference trajectories at global regions except the arbitrary small region around the origin. In particular, constraints on the desired linear and angular velocities as well as the posture of the mobile robot are eliminated unlike the previous studies based on kinematics expressed in polar coordinates. Accordingly, arbitrary trajectories including a circle and a straight line in various forms can be followed even with large initial tracking errors and bounded disturbances. The stability and performance analyzes are performed and also simulations are included to confirm the effectiveness of the proposed scheme.

Swarm-Bot: A New Distributed Robotic Concept

Abstract: The swarm intelligence paradigm has proven to have very interesting properties such as robustness, flexibility and ability to solve complex problems exploiting parallelism and self-organization. Several robotics implementations of this paradigm confirm that these properties can be exploited for the control of a population of physically independent mobile robots. The work presented here introduces a new robotic concept called swarm-bot in which the collective interaction exploited by the swarm intelligence mechanism goes beyond the control layer and is extended to the physical level. This implies the addition of new mechanical functionalities on the single robot, together with new electronics and software to manage it. These new functionalities, even if not directly related to mobility and navigation, allow to address complex mobile robotics problems, such as extreme all-terrain exploration. The work shows also how this new concept is investigated using a simulation tool (swarmbot3d) specifically developed for quickly designing and evaluating new control algorithms. Experimental work shows how the simulated detailed representation of one s-bot has been calibrated to match the behaviour of the real robot.

A design-centred framework for social human-robot interaction

Abstract: Robots currently integrate into our everyday lives, but little is known about how they can act socially. In this paper, we propose a definition of social robots and describe a framework that classifies properties of social robots. The properties consist of form, modality, social norms, autonomy, and interactivity. Finally, we provide broad guidelines for the design of social robots.

Classifying human-robot interaction: an updated taxonomy

Abstract: This paper extends taxonomy of human-robot interaction (HRI) introduced in 2002 to include additional categories as well as updates to the categories from the original taxonomy. New classifications include measures of the social nature of the task (human interaction roles and human-robot physical proximity), task type, and robot morphology.

Simultaneous Localization and Map Building in Large-Scale Cyclic Environments Using the Atlas Framework

Abstract: In this paper we describe Atlas, a hybrid metrical/topological approach to simultaneous localization and mapping (SLAM) that achieves efficient mapping of large-scale environments. The representation is a graph of coordinate frames, with each vertex in the graph representing a local frame and each edge representing the transformation between adjacent frames. In each frame, we build a map that captures the local environment and the current robot pose along with the uncertainties of each. Each map’s uncertainties are modeled with respect to its own frame. Probabilities of entities with respect to arbitrary frames are generated by following a path formed by the edges between adjacent frames, computed using either the Dijkstra shortest path algorithm or breath-first search. Loop closing is achieved via an efficient map-matching algorithm coupled with a cycle verification step. We demonstrate the performance of the technique for post-processing large data sets, including an indoor structured environment (2.2 k...

Effect of a robot on user perceptions

Abstract: Social robots are robots that help people as capable partners rather than as tools, are believed to be of greatest use for applications in entertainment, education, and healthcare because of their potential to be perceived as trusting, helpful, reliable, and engaging. This paper explores how the robot's physical presence influences a person's perception of these characteristics. The first study reported here demonstrates the differences between a robot and an animated character in terms a person's engagement and perceptions of the robot and character. The second study shows that this difference is a result of the physical presence of the robot and that a person's reactions would be similar even if the robot is not physically collocated. Implications to the design of socially communicative and interactive robots are discussed.

Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers

Abstract: Future planetary exploration missions will require wheeled mobile robots ("rovers") to traverse very rough terrain with limited human supervision. Wheel-terrain interaction plays a critical role in rough-terrain mobility. In this paper, an online estimation method that identifies key terrain parameters using on-board robot sensors is presented. These parameters can be used for traversability prediction or in a traction control algorithm to improve robot mobility and to plan safe action plans for autonomous systems. Terrain parameters are also valuable indicators of planetary surface soil composition. The algorithm relies on a simplified form of classical terramechanics equations and uses a linear-least squares method to compute terrain parameters in real time. Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for various soil types.

Coordinated collective motion of Groups of autonomous mobile robots: analysis of Vicsek's model

Abstract: This note gives a qualitative analysis of the dynamics of a system consisting of several mobile robots coordinating their motion using simple local nearest neighbor rules. We show that under some assumptions the headings of all robots will be eventually constant.

Mobile robot navigation using a sensor network

Abstract: We describe an algorithm for robot navigation using a sensor network embedded in the environment. Sensor nodes act as signposts for the robot to follow, thus obviating the need for a map or localization on the part of the robot. Navigation directions are computed within the network (not on the robot) using value iteration. Using small low-power radios, the robot communicates with nodes in the network locally, and makes navigation decisions based on which node it is near. An algorithm based on processing of radio signal strength data was developed so the robot could successfully decide which node neighborhood it belonged to. Extensive experiments with a robot and a sensor network confirm the validity of the approach.

6D SLAM with an application in autonomous mine mapping

Abstract: To create with an autonomous mobile robot a 3D volumetric map of a scene it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. A fast variant of the Iterative Closest Points algorithm registers the 3D scans in a common coordinate system and relocalizes the robot. Finally, consistent 3D maps are generated using a global relaxation. The algorithms have been tested with 3D scans taken in the Mathies mine, Pittsburgh, PA. Abandoned mines pose significant problems to society, yet a large fraction of them lack accurate 3D maps.

Trial by fire [rescue robots]

Abstract: On September 11, 2001, the Center for Robot-Assisted Search and Rescue (CRASAR) responded within six hours to the World Trade Center (WTC) disaster; this is the first known use of robots for urban search and rescue (USAR). The University of South Florida (USF) was one of the four robot teams, and the only academic institution represented. The USF team participated onsite in the search efforts from 12-21 September 2001, collecting and archiving data on the use of all robots, in addition to actively fielding robots. This article provides an overview of the use of robots for USAR, concentrating on what robots were actually used and why. It describes the roles that the robots played in the response and the impact of the physical environment on the platforms. The quantitative and qualitative performance of the robots are summarized in terms of their components (mobility, sensors, control, communications, and power) and within the larger human-robot system. Lessons learned are offered and a synopsis of the current state of rescue robotics and activities at the CRASAR concludes the article.

Movement control algorithms for realization of fault-tolerant ad hoc robot networks

Abstract: Autonomous and semi-autonomous mobile multirobot systems require a wireless communication network in order to communicate with each other and collaboratively accomplish a given task. A multihop communications network that is self-forming, self-healing, and self-organizing is ideally suited for such mobile robot systems that exist in unpredictable and constantly changing environments. However, since every node in a multihop (or ad hoc) network is responsible for forwarding packets to other nodes, the failure of a critical node can result in a network partition. Hence, it is ideal to have an ad hoc network configuration that can tolerate temporary failures while allowing recovery. Since movement of the robot nodes is controllable, it is possible to achieve such fault-tolerant configurations by moving a subset of robots to new locations. In this article we propose a few simple algorithms for achieving the baseline graph theoretic metric of tolerance to node failures, namely, biconnectivity. We formulate an optimization problem for the creation of a movement plan while minimizing the total distance moved by the robots. For one-dimensional networks, we show that the problem of achieving a biconnected network topology can be formulated as a linear program; the latter lends itself to an optimal polynomial time solution. For two-dimensional networks the problem is much harder, and we propose efficient heuristic approaches for achieving biconnectivity. We compare the performance of the proposed algorithms with each other with respect to the total distance moved metric using simulations.

Robot and sensor networks for first responders

Abstract: The need to collect, integrate, and communicate information effectively in emergency response scenarios exceeds the state of the art in information technology. This emergency response problem provides an interesting and important test bed for studying networks of distributed mobile robots and sensors. Here, we describe the component technologies required to deploy a networked-robot system that can augment human firefighters and first responders, significantly enhancing their firefighting capabilities. In a burning building at a firefighting training facility, we deployed a network of stationary Mote sensors, mobile robots with cameras, and stationary radio tags to test their ability to guide firefighters to targets and warn them of potential dangers. Our long-term vision is a physical network that can sense, move, compute, and reason, letting network users (firefighters and first responders) Google for physical information - that is, information about the location and properties of physical objects in the real world.

Modeling and control of a 4-wheel skid-steering mobile robot

Abstract: A mathematical model of a 4-wheel skid-steering mobile robot is presented in a systematic way. The robot is considered as a subsystem consisting of kinematic, dynamic and drive levels. Next, a designing process of a kinematic controller based on the algorithm introduced by (Dixon et al., 2001) is shown. An extension of the kinematic control law at the dynamic and motor levels using the Lyapunov analysis and the backstepping technique is developed. To validate the designed algorithm, extensive simulation results for trajectory tracking and set-point cases are discussed. Some deliberations concerning the tuning of the controller are presented, too.

A knowledge based genetic algorithm for path planning of a mobile robot

Abstract: In this paper, a knowledge based genetic algorithm (GA) for path planning of a mobile robot is proposed, which uses problem-specific genetic algorithms for robot path planning instead of the standard GAs. The proposed knowledge based genetic algorithm incorporates the domain knowledge into its specialized operators, where some also combine a local search technique. The proposed genetic algorithm also features a unique and simple path representation and a simple but effective evaluation method. The knowledge based genetic algorithm is capable of finding an optimal or near-optimal robot path in both complex static and dynamic environments. The effectiveness and efficiency of the proposed genetic algorithm is demonstrated by simulation studies. The irreplaceable role of the specialized genetic operators in the proposed GA for solving robot path planning problem is demonstrated by a comparison study.

Coverage, Exploration and Deployment by a Mobile Robot and Communication Network

Abstract: We consider the problem of coverage and exploration of an unknown dynamic environment using a mobile robot. The environment is assumed to be large enough such that constant motion by the robot is needed to cover the environment. We present an efficient minimalist algorithm which assumes that global information is not available (neither a map, nor GPS). Our algorithm deploys a network of radio beacons which assists the robot in coverage. The network is also used by the robot for navigation. The deployed network can also be used for applications other than coverage (such as multi-robot task allocation). Simulation experiments are presented which show the collaboration between the deployed network and mobile robot for the tasks of coverage/exploration, network deployment and maintenance (repair), and mobile robot recovery (homing behavior). We discuss a theoretical basis for our algorithm on graphs and show the results of the simulated scenario experiments.