Simulators have played a critical role in robotics research as tools for quick and efficient testing of new concepts, strategies, and algorithms. To date, most simulators have been restricted to 2D worlds, and few have matured to the point where they are both highly capable and easily adaptable. Gazebo is designed to fill this niche by creating a 3D dynamic multi-robot environment capable of recreating the complex worlds that would be encountered by the next generation of mobile robots. Its open source status, fine grained control, and high fidelity place Gazebo in a unique position to become more than just a stepping stone between the drawing board and real hardware: data visualization, simulation of remote environments, and even reverse engineering of blackbox systems are all possible applications. Gazebo is developed in cooperation with the Player and Stage projects (Gerkey, B. P., et al., July 2003), (Gerkey, B. P., et al., May 2001), (Vaughan, R. T., et al., Oct. 2003), and is available from http://playerstage.sourceforge.net/gazebo/ gazebo.html.

https://robotics.usc.edu/publications/media/uploads/pubs/394.pdf

Design and use paradigms for Gazebo, an open-source multi-robot simulator

This paper discusses the recursive Bayesian formulation of the simultaneous localization and mapping (SLAM) problem in which probability distributions or estimates of absolute or relative locations of landmarks and vehicle pose are obtained. The paper focuses on three key areas: computational complexity; data association; and environment representation

Simultaneous localization and mapping (SLAM): part II

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.

http://www.gbv.de/dms/hebis-darmstadt/toc/120387220.pdf

Introduction to Autonomous Mobile Robots

Cell phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others relate to coping with fixed focus limitations of cell phone cameras, e.g., in reading digital watermark data. Still others concern user interface improvements. A great number of other features and arrangements are also detailed.

Methods and Systems for Content Processing

We present a system that estimates the motion of a stereo head or a single moving camera based on video input. The system operates in real-time with low delay and the motion estimates are used for navigational purposes. The front end of the system is a feature tracker. Point features are matched between pairs of frames and linked into image trajectories at video rate. Robust estimates of the camera motion are then produced from the feature tracks using a geometric hypothesize-and-test architecture. This generates what we call visual odometry, i.e. motion estimates from visual input alone. No prior knowledge of the scene nor the motion is necessary. The visual odometry can also be used in conjunction with information from other sources such as GPS, inertia sensors, wheel encoders, etc. The pose estimation method has been applied successfully to video from aerial, automotive and handheld platforms. We focus on results with an autonomous ground vehicle. We give examples of camera trajectories estimated purely from images over previously unseen distances and periods of time.

Visual odometry

This paper presents further improvements on the earlier vector field histogram (VFH) method developed by Borenstein-Koren (1991) for real-time mobile robot obstacle avoidance. The enhanced method, called VFH+, offers several improvements that result in smoother robot trajectories and greater reliability. VFH+ reduces some of the parameter tuning of the original VFH method by explicitly compensating for the robot width. Also added in VFH+ is a better approximation of the mobile robot trajectory, which results in higher reliability.

/pdf/vfh-reliable-obstacle-avoidance-for-fast-mobile-robots-1lljyelted.pdf

VFH+: reliable obstacle avoidance for fast mobile robots

This paper presents a new appearance-based place recognition system for topological localization. The method uses a panoramic vision system to sense the environment. Color images are classified in real-time based on nearest-neighbor learning, image histogram matching, and a simple voting scheme. The system has been evaluated with eight cross-sequence tests in four unmodified environments, three indoors and one outdoors. In all eight cases, the system successfully tracked the mobile robot's position. The system correctly classified between 87% and 98% of the input color images. For the remaining images, the system was either momentarily confused or uncertain, but never classified an image incorrectly.

/pdf/appearance-based-place-recognition-for-topological-44h99tdrb1.pdf

Appearance-based place recognition for topological localization

This paper presents an enhancement to the earlier developed vector field histogram (VFH) method for mobile robot obstacle avoidance. The enhanced method, called VFH/sup */ successfully deals with situations that are problematic for purely local obstacle avoidance algorithms. The VFH/sup */ method verifies that a particular candidate direction guides the robot around an obstacle. The verification is performed by using the A/sup */ search algorithm and appropriate cost and heuristic functions.

/pdf/vfh-sup-local-obstacle-avoidance-with-look-ahead-1mky5yntxf.pdf

VFH/sup */: local obstacle avoidance with look-ahead verification

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.

/pdf/appearance-based-obstacle-detection-with-monocular-color-3j5kkq9940.pdf

Appearance-Based Obstacle Detection with Monocular Color Vision

This paper introduces the GuideCane, a novel device designed to help blind or visually impaired travellers to navigate safely and quickly among obstacles and other hazards faced by blind pedestrians. The GuideCane, currently under development at the University of Michigan's Mobile Robotics Lab, comprises of a long handle and a "sensor head" unit that is attached at the distal end of the handle. The sensor head is mounted on a steerable but unpowered two-wheeled steering axle. During operation, the user pushes the lightweight GuideCane ahead of him/her. Ultrasonic sensors mounted on the sensor head detect obstacles and steer the device around it. The user feels the steering command as a very noticeable physical force through the handle and is able to follow the GuideCane's path easily and without any conscious effort.

/pdf/the-guidecane-a-computerized-travel-aid-for-the-active-3o13h0uxql.pdf

Iwan Ulrich

Papers

VFH+: reliable obstacle avoidance for fast mobile robots

Appearance-based place recognition for topological localization

VFH/sup */: local obstacle avoidance with look-ahead verification

Appearance-Based Obstacle Detection with Monocular Color Vision

The GuideCane-a computerized travel aid for the active guidance of blind pedestrians