Mobile robot navigation

About: Mobile robot navigation is a research topic. Over the lifetime, 14713 publications have been published within this topic receiving 263092 citations.

Mobile robot navigation using artificial landmarks

Abstract: This article describes a landmark-based navigation technique for a mobile robot. Robot position estimation is achieved by using a camera and a navigational landmark pattern, which consists of simple geometrical patterns. The Modified Elliptical Hough Transform (MEHT) is developed for detecting and measuring the projection of the landmark in the camera's image space. Robustness of this approach is demonstrated by studying the cases of noisy image data and partial occlusion of the landmark pattern. Error analysis of MEHT is performed to provide more understanding of the effects of applying elliptical approximation to the projection of a circular pattern. © 1997 John Wiley & Sons, Inc.

Simple yet stable bearing-only navigation

Abstract: This article describes a simple monocular navigation system for a mobile robot based on the map-and-replay technique. The presented method is robust and easy to implement and does not require sensor calibration or structured environment, and its computational complexity is independent of the environment size. The method can navigate a robot while sensing only one landmark at a time, making it more robust than other monocular approaches. The aforementioned properties of the method allow even low-cost robots to effectively act in large outdoor and indoor environments with natural landmarks only. The basic idea is to utilize a monocular vision to correct only the robot's heading, leaving distance measurements to the odometry. The heading correction itself can suppress the odometric error and prevent the overall position error from diverging. The influence of a map-based heading estimation and odometric errors on the overall position uncertainty is examined. A claim is stated that for closed polygonal trajectories, the position error of this type of navigation does not diverge. The claim is defended mathematically and experimentally. The method has been experimentally tested in a set of indoor and outdoor experiments, during which the average position errors have been lower than 0.3 m for paths more than 1 km long. © 2010 Wiley Periodicals, Inc.

Systems and Methods for Capturing Images and Annotating the Captured Images with Information

Abstract: The present teachings provide an autonomous mobile robot that includes a drive configured to maneuver the robot over a ground surface within an operating environment; a camera mounted on the robot having a field of view including the floor adjacent the mobile robot in the drive direction of the mobile robot; a frame buffer that stores image frames obtained by the camera while the mobile robot is driving; and a memory device configured to store a learned data set of a plurality of descriptors corresponding to pixel patches in image frames corresponding to portions of the operating environment and determined by mobile robot sensor events.

Integrating reaction and planning in a heterogeneous asynchronous architecture for mobile robot navigation

Abstract: We present an architecture for controlling autonomous mobile robots based on control of continuous activities (processes) rather than discrete actions. We define a hierarchy of activity, and argue that different levels of activities require different sorts of computational mechanisms to control them. Many controversial issues concerning the use of persistent internal state and higher levels of abstraction can be better understood in terms of this hierarchy. Two experiments using the architecture to control mobile robots performing complex navigation tasks are described.

Social robot navigation

Abstract: Mobile robots that encounter people on a regular basis must react to them in some way. While traditional robot control algorithms treat all unexpected sensor readings as objects to be avoided, we argue that robots that operate around people should react socially to those people, following the same social conventions that people use around each other. This thesis presents our COMPANION framework: a Constraint-Optimizing Method for Person-Acceptable NavigatION. COMPANION is a generalized framework for representing social conventions as components of a constraint optimization problem, which is used for path planning and navigation. Social conventions, such as personal space and tending to the right, are described as mathematical cost functions that can be used by an optimal path planner. These social conventions are combined with more traditional constraints, such as minimizing distance, in a flexible way, so that additional constraints can be added easily. We present a set of constraints that specify the social task of traveling around people. We explore the implementation of this task first in simulation, where we demonstrate a robot's behavior in a wide variety of scenarios. We also detail how a robot's behavior can be changed by using different relative weights between the constraints or by using constraints representing different sociocultural conventions. We then explore the specific case of passing a person in a hallway, using the robot Grace. Through a user study, we show that people interpret the robot's behavior according to human social norms, and also that people ascribe different personalities to the robot depending on its level of social behavior. In addition, we present an extension of the COMPANION framework that is able to represent joint tasks between the robot and a person. We identify the constraints necessary to represent the task of having a robot escort a person while traveling side-by-side. In simulation, we show the capability of this representation to produce behaviors such as speeding up or slowing down to travel together around corners, as well as complex maneuvers to travel through narrow chokepoints and return to a side-by-side formation. Finally, we present a newly designed robot, Companion, that is intended as a platform for general social human-robot research. Companion is a holonomic robot, able to move sideways without turning first, which we believe is an important social capability. We detail the design and capabilities of this new platform. As a whole, this thesis demonstrates both a need for, and an implementation and evaluation of, robots that navigate around people according to social norms.