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Inertial navigation system

About: Inertial navigation system is a research topic. Over the lifetime, 14582 publications have been published within this topic receiving 190618 citations. The topic is also known as: intertial guidance system & inertial reference platform.


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Patent
01 Jul 2003
TL;DR: A method and system for automatically activating a train warning device that uses a positioning system such as a global positioning system (GPS) receiver or an inertial navigation system (INS) to determine the train's position is presented in this article.
Abstract: A method and system for automatically activating a train warning device that uses a positioning system such as a global positioning system (GPS) receiver or an inertial navigation system (INS) to determine the train's position. The system further includes a database containing locations of grade crossings and other locations at which a train is required to give a warning signal and what regulations govern activation of the warning device at such locations.

91 citations

Proceedings ArticleDOI
25 Aug 2001
TL;DR: In this article, the feasibility of designing a gyroscope-free inertial navigation system (INS) that uses only accelerometers to compute the linear and angular motions of a rigid body relative to a fixed inertial frame is examined.
Abstract: We examine the feasibility of designing a gyroscope-free inertial navigation system (INS) that uses only accelerometers to compute the linear and angular motions of a rigid body. The accelerometer output equation is derived to relate the linear and angular motions of a rigid body relative to a fixed inertial frame. A sufficient condition is given to determine if a configuration of accelerometers is feasible. If the condition is satisfied, the angular and linear motions can be computed separately using two decoupled equations of an input-output (I/O) dynamical system; a state equation for angular velocity and an output equation for linear acceleration. This simple computation scheme is derived from the corresponding dynamical system equations for a special cube configuration for which the angular acceleration is expressed as a linear combination of the accelerometer outputs.

91 citations

Journal ArticleDOI
TL;DR: In this paper, a vision-based obstacle detection and navigation system for use as part of a robotic solution for the sustainable intensification of broad-acre agriculture is described, including detailed descriptions of three key parts of the system: novelty-based obstacles detection, visually-aided guidance, and a navigation system that generates collision-free kinematically feasible paths.
Abstract: This paper describes a vision-based obstacle detection and navigation system for use as part of a robotic solution for the sustainable intensification of broad-acre agriculture. To be cost-effective, the robotics solution must be competitive with current human-driven farm machinery. Significant costs are in high-end localization and obstacle detection sensors. Our system demonstrates a combination of an inexpensive global positioning system and inertial navigation system with vision for localization and a single stereo vision system for obstacle detection. The paper describes the design of the robot, including detailed descriptions of three key parts of the system: novelty-based obstacle detection, visually-aided guidance, and a navigation system that generates collision-free kinematically feasible paths. The robot has seen extensive testing over numerous weeks of field trials during the day and night. The results in this paper pertain to one particular 3 h nighttime experiment in which the robot performed a coverage task and avoided obstacles. Additional results during the day demonstrate that the robot is able to continue operating during 5 min GPS outages by visually following crop rows.

91 citations

Patent
13 Sep 1994
TL;DR: In this article, the authors proposed a navigation and attitude determination solution by means of a Kalman filter process wherein the observables comprise measured phase double-differences and each predicted phase double difference is obtained by operating on the Kalman state vector with an observation matrix defined by linearizing the equations relating the phase doubledifference to the navigation states.
Abstract: The navigation apparatus with improved attitude determination is intended for use on a mobile platform. It combines data from a platform inertial navigation unit and carrier phase data for a plurality of GPS satellite signals received at a plurality of receiving points on the platform for the purpose of obtaining estimates of the navigation states of the platform. The navigation apparatus comprises a processor which computes estimates of the states from inputs comprising (1) one or more measured phase double-differences calculated from the measured satellite signal carrier phases, (2) the estimated position of the platform, (3) the estimated positions of the receiving points, and (4) the positions of the satellites, a phase double-difference being defined as the difference in phase differences for signals received from two satellites and a phase difference being defined as the difference in carrier phase of a satellite signal received at two receiving points. The navigation and attitude determination solution is obtained by means of a Kalman filter process wherein the observables comprise measured phase double-differences and each predicted phase double-difference is obtained by operating on the Kalman state vector with an observation matrix defined by linearizing the equations relating the phase double-difference to the navigation states.

91 citations

Proceedings ArticleDOI
26 Jul 1993
TL;DR: The results show that with careful and detailed modeling of error sources, low cost inertial sensing systems can provide valuable position information.
Abstract: A low-cost, solid-state inertial navigation system for robotics applications is described. Error models for the inertial sensors are generated and included in an extended Kalman filter (EKF) for estimating the position and orientation of a moving robot vehicle. A solid-state gyroscope and an accelerometer have been evaluated. Without error compensation, the error in orientation is between 5-15/spl deg//min but can be improved at least by a factor of five if an adequate error model is supplied. Similar error models have been developed for each axis of a solid-state triaxial accelerometer. Linear position estimation with accelerometers and tilt sensors is more susceptible to errors due to the double integration process involved in estimating position. WIth the system described here, the position drift rate is 1-8 cm/s, depending on the frequency of acceleration changes. The results show that with careful and detailed modeling of error sources, low cost inertial sensing systems can provide valuable position information.

91 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023309
2022657
2021491
2020889
20191,003
20181,013