Showing papers on "Mobile robot navigation published in 2011"

Autonomous multi-floor indoor navigation with a computationally constrained MAV

Abstract: In this paper, we consider the problem of autonomous navigation with a micro aerial vehicle (MAV) in indoor environments. In particular, we are interested in autonomous navigation in buildings with multiple floors. To ensure that the robot is fully autonomous, we require all computation to occur on the robot without need for external infrastructure, communication, or human interaction beyond high-level commands. Therefore, we pursue a system design and methodology that enables autonomous navigation with real-time performance on a mobile processor using only onboard sensors. Specifically, we address multi-floor mapping with loop closure, localization, planning, and autonomous control, including adaptation to aerodynamic effects during traversal through spaces with low vertical clearance or strong external disturbances. We present experimental results with ground truth comparisons and performance analysis.

Mobile robot system

Abstract: A robot system (1600) includes a mobile robot (100) having a controller (500) executing a control system (510) for controlling operation of the robot, a cloud computing service (1620) in communication with the controller of the robot, and a remote computing device (310) in communication with the cloud computing service. The remote computing device communicates with the robot through the cloud computing service.

Personal wireless navigation system

Abstract: A personal wireless navigation system operable on wireless phone devices provides a platform for empowering a merchant-paid search. Performance of a navigation functionality in a personal wireless navigation system is higher and more comparable and competitive with portable navigation devices and in-car navigation systems, and the search capability is comparable and competitive with the most popular web search engines. A user interface (UI) and look and feel of the personal wireless navigation system is provided which is enhanced so that users do not simply want to use the product—they covet it. The personal wireless navigation system may be constructed such that a subset of it with fewer features and functions can be productized, marketed and deployed to users.

Reciprocal collision avoidance with acceleration-velocity obstacles

Abstract: We present an approach for collision avoidance for mobile robots that takes into account acceleration constraints. We discuss both the case of navigating a single robot among moving obstacles, and the case of multiple robots reciprocally avoiding collisions with each other while navigating a common workspace. Inspired by the concept of velocity obstacles [3], we introduce the acceleration-velocity obstacle (AVO) to let a robot avoid collisions with moving obstacles while obeying acceleration constraints. AVO characterizes the set of new velocities the robot can safely reach and adopt using proportional control of the acceleration. We extend this concept to reciprocal collision avoidance for multi-robot settings, by letting each robot take half of the responsibility of avoiding pairwise collisions. Our formulation guarantees collision-free navigation even as the robots act independently and simultaneously, without coordination. Our approach is designed for holonomic robots, but can also be applied to kinematically constrained non-holonomic robots such as cars. We have implemented our approach, and we show simulation results in challenging environments with large numbers of robots and obstacles.

Reinforcement based mobile robot navigation in dynamic environment

Abstract: In this paper, a new approach is developed for solving the problem of mobile robot path planning in an unknown dynamic environment based on Q-learning. Q-learning algorithms have been used widely for solving real world problems, especially in robotics since it has been proved to give reliable and efficient solutions due to its simple and well developed theory. However, most of the researchers who tried to use Q-learning for solving the mobile robot navigation problem dealt with static environments; they avoided using it for dynamic environments because it is a more complex problem that has infinite number of states. This great number of states makes the training for the intelligent agent very difficult. In this paper, the Q-learning algorithm was applied for solving the mobile robot navigation in dynamic environment problem by limiting the number of states based on a new definition for the states space. This has the effect of reducing the size of the Q-table and hence, increasing the speed of the navigation algorithm. The conducted experimental simulation scenarios indicate the strength of the new proposed approach for mobile robot navigation in dynamic environment. The results show that the new approach has a high Hit rate and that the robot succeeded to reach its target in a collision free path in most cases which is the most desirable feature in any navigation algorithm.

Comparison of Embedded System Design for Industrial Applications

Abstract: This paper presents a survey on embedded systems design and applications. Several platforms for embedded systems, including microcontrollers, microprocessors, field-programmable gate arrays, digital signal processors, and application-specific integrated circuits are discussed and compared. A survey of embedded system-based industrial applications is presented. Examples of real-life design decisions specific to development of such systems are also presented. The carefully selected three design case study examples include industrial control of wind tunnel with emphasis on actuator control, a mobile robot navigation system with emphasis on integration and synchronization of several subsystems, and optimized implementation of computationally intensive control system on a small microcontroller system.

Intelligent Robotics and Applications

Abstract: This volume constitutes the refereed proceedings of the Second International Conference on Intelligent Robotics and Applications, ICIRA 2009, held in Singapore, in December 2009. The 128 revised full papers presented were thoroughly reviewed and selected from 173 submissions. They are organized in topical sections on ubiquitous and cooperative robots in smart space; advanced control on autonomous vehicles; intelligent vehicles: perception for safe navigation; novel techniques for collaborative driver support; robot and automation in tunneling; robot mechanism and design; robot motion analysis; robot motion control; visual perception by robots; computational intelligence by robots; robot and application; and robot and investigation.

Evolutionary-Group-Based Particle-Swarm-Optimized Fuzzy Controller With Application to Mobile-Robot Navigation in Unknown Environments

Abstract: This paper proposes an evolutionary-group-based particle-swarm-optimization (EGPSO) algorithm for fuzzy-controller (FC) design. The EGPSO uses a group-based framework to incorporate crossover and mutation operations into particle-swarm optimization. The EGPSO dynamically forms different groups to select parents in crossover operations, particle updates, and replacements. An adaptive velocity-mutated operation (AVMO) is incorporated to improve search ability. The EGPSO is applied to design all of the free parameters in a zero-order Takagi-Sugeno-Kang (TSK)-type FC. The objective of EGPSO is to improve fuzzy-control accuracy and design efficiency. Comparisons with different population-based optimizations of fuzzy-control problems demonstrate the superiority of EGPSO performance. In particular, the EGPSO-designed FC is applied to mobile-robot navigation in unknown environments. In this application, the robot learns to follow object boundaries through an EGPSO-designed FC. A simple learning environment is created to build this behavior without an exhaustive collection of input-output training pairs in advance. A behavior supervisor is proposed to combine the boundary-following behavior and the target-seeking behavior for navigation, and the problem of dead cycles is considered. Successful mobile-robot navigation in simulation and real environments verifies the EGPSO-designed FC-navigation approach.

Human-Centered Robot Navigation—Towards a Harmoniously Human–Robot Coexisting Environment

Abstract: This paper proposes a navigation algorithm that considers the states of humans and robots in order to achieve harmonious coexistence between them. A robot navigation in the presence of humans and other robots is rarely considered in the field of robotics. When navigating through a space filled with humans and robots with different functions, a robot should not only pay attention to obstacle avoidance and goal seeking, it should also take into account whether it interferes with other people or robots. To deal with this problem, we propose several harmonious rules, which guarantee a safe and smooth navigation in a human-robot environment. Based on these rules, a practical navigation method-human-centered sensitive navigation (HCSN)-is proposed. HCSN considers the fact that both humans and robots have sensitive zones, depending on their security regions or on a human's psychological state. We model these zones as various sensitive fields with priorities, whereby robots tend to yield socially acceptable movements.

Application of Dijkstra algorithm in robot path-planning

Abstract: In this paper, the robot is a maze robot. Dijkstra algorithm is used in the robot path planning. The shortest path is selected in the process of barrier. Simulation results prove the model valid; it can effectively solve the maze robot path planning.

Mobile robot navigation and target tracking system

Abstract: This paper presents the framework for the navigation and target tracking system for a mobile robot. Navigation and target tracking are to be performed using a Microsoft Xbox Kinect sensor which provides RGB color and 3D depth imaging data to an x86 based computer onboard the robot running Ubuntu Linux. A fuzzy logic controller to be implemented on the computer is considered for control of the robot in obstacle avoidance and target following. Data collected by the computer is to be sent to a server for processing with learning-based systems utilizing neural networks for pattern recognition, object tracking, long-term path planning and process improvement. An eventual goal of this work is to create a multi-agent robot system that is able to work autonomously in an outdoor environment.

Towards semantic robot description languages

Abstract: There is a semantic gap between simple but high-level action instructions like “Pick up the cup with the right hand” and low-level robot descriptions that model, for example, the structure and kinematics of a robot's manipulator. Currently, programmers bridge this gap by mapping abstract instructions to parametrized algorithms and rigid body parts of a robot within their control programs. By linking descriptions of robot components, i.e. sensors, actuators and control programs, via capabilities to actions in an ontology we equip robots with knowledge about themselves that allows them to infer the required components for performing a given action. Thereby a robot that is instructed by an end-user, a programmer, or even another robot to perform a certain action, can assess itself whether it is able and how to perform the requested action. This self-knowledge for robots could considerably change the way of robot control, robot interaction, robot programming, and multi-robot communication.

An improved Artificial Potential Field approach to real-time mobile robot path planning in an unknown environment

Abstract: This paper deals with the navigation of a mobile robot in an unknown environment. The approach developed is based on the Artificial Potential Field (APF) method in which the target creates a virtual potential that attracts the robot while obstacles create a virtual potential that repels the robot. A new form of repelling potential is proposed in order to reduce oscillations and to avoid conflicts when the target is close to obstacles. A rotational force is integrated as well, allowing for a smoother trajectory around the obstacles. Experiment results show the effectiveness of the proposed approach.

ROS-based mapping, localization and autonomous navigation using a Pioneer 3-DX robot and their relevant issues

Abstract: The Robot Operating System (ROS) provides operating system-like services to operate robots. Mapping, localization, and autonomous navigation in an indoor environment are popular issues in the field of autonomous robots. Autonomous navigation in a dynamic environment is not only challenging but also uncovers many indoor environmental factors which affect the process of mapping and navigation. The presented work describes how a ROS-based control system is used with a Pioneer 3-DX robot for indoor mapping, localization, and autonomous navigation. Mapping of different challenging environments is presented in this work. Moreover, some factors associated with indoor environments that can affect mapping, localization, and automatic navigation, are also presented. For experiments, three environments (one artificial and two real) have been tested. Some implementation was done in C and Python.

Development of an Indoor Navigation System Using NFC Technology

Abstract: Existing indoor navigation systems face with many different technical and usability problems. In this paper we present a Near Field Communication (NFC) based indoor navigation system called NFC Internal in order to eliminate the current indoor navigation problems. NFC Internal enables an easy data transfer for indoor navigation systems just by touching tags spread over a building or a complex. The proposed system has several benefits and has potential to increase the usability of these systems. We discuss the system requirements and explain the phases of NFC Internal through use cases.

Multi-state model for robot and user interaction

Abstract: The subject disclosure is directed towards a robot device including a model that controls a robot's task-related operations to perform tasks and user-engagement operations to interact with the robot. The model controls the operating states, including transitioning from an autonomous task state to an engaged state based on current context determined from various stimuli, e.g., information received via sensors of the robot and/or learned data. The robot may seek to engage the user, the user may seek to engage the robot, or the user and robot may meet by chance in which either may attempt to initiate the engagement.

Understanding human interaction for probabilistic autonomous navigation using Risk-RRT approach

Abstract: With the growing demand of personal assistance to mobility and mobile service robotics, robot navigation systems must be “aware” of the social conventions followed by people. They must respect proximity constraints but also respect people interacting. For example, they may not break interaction between people talking, unless the occupants want to take part in the conversation. In this case, they must be able to join the group using a socially adapted behavior. This paper proposes a risk-based navigation method including both the traditional notion of risk of collision and the notion of risk of disturbance. Results exhibit new emerging behavior showing how a robot takes into account social conventions in its navigation strategy.

System and method for robust calibration between a machine vision system and a robot

Abstract: A system and method for robustly calibrating a vision system and a robot is provided. The system and method enables a plurality of cameras to be calibrated into a robot base coordinate system to enable a machine vision/robot control system to accurately identify the location of objects of interest within robot base coordinates.

Monocular Visual Odometry using a Planar Road Model to Solve Scale Ambiguity

Abstract: Precise knowledge of a robots’s ego-motion is a crucial requirement for higher level tasks like autonomous navigation. Bundle adjustment based monocular visual odometry has proven to successfully estimate the motion of a robot for short sequences, but it suffers from an ambiguity in scale. Hence, approaches that only optimize locally are prone to drift in scale for sequences that span hundreds of frames. In this paper we present an approach to monocular visual odometry that compensates for drift in scale by applying constraints imposed by the known camera mounting and assumptions about the environment. To this end, we employ a continuously updated point cloud to estimate the camera poses based on 2d-3dcorrespondences. Within this set of camera poses, we identify keyframes which are combined into a sliding window and refined by bundle adjustment. Subsequently, we update the scale based on robustly tracked features on the road surface. Results on real datasets demonstrate a significant increase in accuracy compared to the non-scaled scheme.

Communication assisted navigation in robotic swarms: Self-organization and cooperation

Abstract: We present a communication based navigation algorithm for robotic swarms. It lets robots guide each other's navigation by exchanging messages containing navigation information through the wireless network formed among the swarm. We study the use of this algorithm in two different scenarios. In the first scenario, the swarm guides a single robot to a target, while in the second, all robots of the swarm navigate back and forth between two targets. In both cases, the algorithm provides efficient navigation, while being robust to failures of robots in the swarm. Moreover, we show that in the latter case, the system lets the swarm self-organize into a robust dynamic structure. This self-organization further improves navigation efficiency, and is able to find shortest paths in cluttered environments. We test our system both in simulation and on real robots.

Magnetic field-based SLAM method for solving the localization problem in mobile robot floor-cleaning task

Abstract: In this paper we present a SLAM method based on indoor magnetic field anomalies and measure the acquired map quality in the context of the localization problem present in mobile robot floor-cleaning scenarios. According to our real-world robot experiments in different environments, it appears that most modern buildings have sufficient magnetic field variation to make the method applicable in mobile robot floor-cleaning tasks. We show that our method can be used to acquire maps that are accurate enough to be utilized in the robot coverage problem, thus reducing over-cleaning. We use Gaussian Processes to model the magnetic field and a Rao-Blackwellized Particle Filter to estimate the pose distribution of the robot. Because magnetic field anomalies are not correlated to typical features used in localization, our method can handle many situations in which other methods fail. The minimalistic sensory requirements of our method make it a very viable alternative for low-cost domestic robots.

A review of control architectures for autonomous navigation of mobile robots

Abstract: A mobile robot as an intelligent system needs to sense the surroundings, perceive the working environment, plan a trajectory and execute proper reaction using the information. Robotic control architectures define how these abilities should be integrated to construct and develop an autonomous navigation. The control architectures could be classified into three categories: Deliberative (Centralized) navigation, Reactive (Behaviour-based) navigation and hybrid (Deliberative - Reactive) navigation. This paper reviews various control architectures for autonomous navigation of mobile robots. The significance, advantages and drawbacks of the architectures are discussed and compared with each other. Key words: Intelligent system, mobile robot, autonomous navigation, control architecture.

Automatic Deployment of Robotic Teams

Abstract: A major goal in robot motion planning and control is to be able to specify a task in a high-level, expressive language and have the robot(s) to automatically convert the specification into a set of low-level primitives, such as feedback controllers and communication protocols, to accomplish the task. The robots can vary from manipulator arms used in manufacturing or surgery, to autonomous vehicles used in search and rescue or in planetary exploration, and to smart wheel chairs for disabled people. They are subject to mechanical constraints (e.g., a carlike robot cannot move sideways,an airplane cannot stop in place) and have limited computation, sensing, and communication capabilities. The environments can be cluttered with possibly moving and shape-changing obstacles and can con tain dynamic (moving, appearing, or disappearing) targets. One of the major challenges in this area is the development of a computationally efficient frame work accommodating both the robot constraints and the complexity of the environment, while, at the same time, allowing for a large spectrum of task specifications.

A smooth control law for graceful motion of differential wheeled mobile robots in 2D environment

Abstract: Although recent progress in 2D mobile robot navigation has been significant, the great majority of existing work focuses only on ensuring that the robot reaches its goal. But to make autonomous navigation truly successful, the “quality” of planned motion is important as well. Here, we develop and analyze a pose-following kinematic control law applicable to unicycle-type robots, such that the robot can generate intuitive, fast, smooth, and comfortable trajectories.

Guided Navigation Through Geo-Located Panoramas

Abstract: A capability for guided navigation in an interactive virtual three-dimensional environment is provided. Such a capability may enhance user experience by providing the feeling of free- form navigation to a user. It may be necessary to constrain the user to certain areas of good visual quality, and subtly guide the user towards viewpoints with better rendering results without disrupting the metaphor of freeform navigation. Additionally, such a capability may enable users to "drive" down a street, follow curving roads, and turn around intersections within the interactive virtual three-dimensional environment. Further, this capability may be applicable to image-based rendering techniques in addition to any three-dimensional graphics system that incorporates navigation based on road networks and/or paths.

Ground vehicle navigation in harsh urban conditions by integrating inertial navigation system, global positioning system, odometer and vision data

Abstract: Combining GPS/INS/odometer data has been considered one of the most attractive methodologies for ground vehicle navigation. In the case of long GPS signal blockages inherent to complex urban environments, however, the accuracy of this approach is largely deteriorated. To overcome this limitation, this study proposes a novel ground vehicle navigation system that combines INS, odometer and omnidirectional vision sensor. Compared to traditional cameras, omnidirectional vision sensors can acquire much more information from the environment thanks to their wide field of view. The proposed system automatically extracts and tracks vanishing points in omnidirectional images to estimate the vehicle rotation. This scheme provides robust navigation information: specifically by combining the advantages of vision, odometer and INS, we estimate the attitude without error accumulation and at a fast running rate. The accurate rotational information is fed back into a Kalman filter to improve the quality of the INS bridging in harsh urban conditions. Extensive experiments have demonstrated that the proposed approach significantly reduces the accumulation of position, velocity and attitude errors during simulated GPS outages. Specifically, the position accuracy is improved by over 30% during simulated GPS outages.

Mobile Robots: Navigation, Control and Remote Sensing

Abstract: mobile robots. navigation, control and remote sensing mobile robots navigation control and remote sensing mobile robots navigation control and remote sensing mobile robots navigation control and remote sensing mobile robots navigation control and remote sensing remote navigation of a mobile robot in an rfid-augmented mobile robots navigation control and remote sensing full multi-robot system for real-time sensing and monitoring mobile robots download.e-bookshelf mobile robot navigation using active vision design and implementation of a mobile agricultural robot remote control of on-line mobile robots over ip networks chapter 1 mobile robots for polar remote sensing mobile robot navigation and control: a case study mit 3d-camera based navigation of a mobile robot in an mobile robot navigationtechniques: asurvey ijraset autonomous mobile robot research at louisiana state control architecture for mobile robot teleoperation target tracking control of mobile robot based on intelligent mobile robot motion control in unstructured mobile robots as remote sensors for spatial point process autonomous navigation and teleoperation in robots using computer vision for mobile robot navigation uni-stuttgart control of mobile robots through wireless sensor networks robotic navigation and mapping with radar robotic gx developer operating manual browserfame anfis approach for navigation of mobile robots polaris outlaw 50 repair manual ebook | browserfame wireless sensor-driven intelligent navigation method for syllabus for ece 450: introduction to robotics section 001 ece624 schedule of topics george mason university mobile robots with in -situ and remote sensors for real mobile robot navigation in narrow aisles with ultrasonic sensor-based intelligent mobile robot navigation in development of fieldbus architecture for teleoperation and a new vision for smart objects and the internet of things design and implementation of a control system for a networked robots: flying robot navigation using a sensor net inter-row robot navigation using 1d ranging sensors an architecture for distributed environment sensing with the mysteries of udolpho; and, a sicilian romance by ann dual-robot navigation system for real-time