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

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.

/pdf/nearness-diagram-nd-navigation-collision-avoidance-in-593t4ziv16.pdf

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

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

The GuideCane is a device designed to help blind or visually impaired users navigate safely and quickly among obstacles and other hazards. During operation, the user pushes the lightweight GuideCane forward. When the GuideCane's ultrasonic sensors detect an obstacle, the embedded computer determines a suitable direction of motion that steers the GuideCane and the user around it. The steering action results in a very noticeable force felt in the handle, which easily guides the user without any conscious effort on his/her part.

/pdf/the-guidecane-applying-mobile-robot-technologies-to-assist-41hezlzpk2.pdf

The GuideCane-applying mobile robot technologies to assist the visually impaired

In this paper, we describe our autonomous vision-based quadrotor MAV system which maps and explores unknown environments. All algorithms necessary for autonomous mapping and exploration run on-board the MAV. Using a front-looking stereo camera as the main exteroceptive sensor, our quadrotor achieves these capabilities with both the Vector Field Histogram+ (VFH+) algorithm for local navigation, and the frontier-based exploration algorithm. In addition, we implement the Bug algorithm for autonomous wall-following which could optionally be selected as the substitute exploration algorithm in sparse environments where the frontier-based exploration under-performs. We incrementally build a 3D global occupancy map on-board the MAV. The map is used by the VFH+ and frontier-based exploration in dense environments, and the Bug algorithm for wall-following in sparse environments. During the exploration phase, images from the front-looking camera are transmitted over Wi-Fi to the ground station. These images are input to a large-scale visual SLAM process running off-board on the ground station. SLAM is carried out with pose-graph optimization and loop closure detection using a vocabulary tree. We improve the robustness of the pose estimation by fusing optical flow and visual odometry. Optical flow data is provided by a customized downward-looking camera integrated with a microcontroller while visual odometry measurements are derived from the front-looking stereo camera. We verify our approaches with experimental results.

Vision-based autonomous mapping and exploration using a quadrotor MAV

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

J. Borenstein

Papers

VFH+: reliable obstacle avoidance for fast mobile robots