Autonomous vehicle navigation with real-time 3D laser based positioning for construction

Beliveau, Yvan J.; Fithian, Jeffrey E.; Deisenroth, Michael P.

doi:10.1016/s0926-5805(96)00140-9

Cited by 28 publications

(14 citation statements)

References 13 publications

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“…The difficulty with this system is the setup of the networked beacons. The SPSi Odyssey system (used by Beliveau et al [4]) is different, since it can position a mobile in 3D. The beacons are laser transmitters and the receiver is located on the mobile robot.…”

Section: A Commercial Systemsmentioning

confidence: 99%

BeAMS: A Beacon-Based Angle Measurement Sensor for Mobile Robot Positioning

Pierlot

Droogenbroeck

2014

IEEE Trans. Robot.

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Abstract-Positioning is a fundamental issue in mobile robot applications, and it can be achieved in multiple ways. Among these methods, triangulation based on angle measurements is widely used, robust, accurate, and flexible. This paper presents BeAMS, a new active beacon-based angle measurement system used for mobile robot positioning.BeAMS introduces several major innovations. One innovation is the use of a unique unsynchronized channel with On-Off Keying modulated infrared signals to measure angles and to identify the beacons. We also introduce a new mechanism to measure angles: our system detects a beacon when it enters and leaves an angular window. We show that the estimator resulting from the center of this angular window provides an unbiased estimate of the beacon angle. A theoretical framework for a thorough performance analysis of BeAMS is provided. We establish the upper bound of the variance and validate this bound through experiments and simulations; the overall error measure of BeAMS is lower than 0.24 deg for an acquisition rate of 10 Hz.In conclusion, BeAMS is a low power, flexible, and robust solution for angle measurement, and a reliable component for robot positioning.

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Section: A Commercial Systemsmentioning

confidence: 99%

BeAMS: A Beacon-Based Angle Measurement Sensor for Mobile Robot Positioning

Pierlot

Droogenbroeck

2014

IEEE Trans. Robot.

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“…Apart from HRI as a midway solution, many researchers have realized that to increase the level of autonomy for construction robots, the mapping and navigation abilities of the robot are essential (Beliveau et al, 1996;Forsberg et al, 1997;Shohet & Rosenfeld, 1997). However, the accuracy of simultaneous localization and mapping (SLAM) algorithm is found to be insufficient at that time for many construction tasks which require direct manipulation of construction materials or tools (Shohet & Rosenfeld, 1997).…”

Section: Related Workmentioning

confidence: 99%

Human-Robot Integration for Pose Estimation and Semi-Autonomous Navigation on Unstructured Construction Sites

Feng¹,

Fredricks

Kamat

2013

Proceedings of the 30th International Symposium on Automation and Robotics in Construction and Mining (ISARC 2013): Building Th

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Compared to widespread successful deployment of robotic manipulators for repetitive and hazardous tasks in related industries such as manufacturing, the construction industry has achieved relatively limited benefits from robotics and soft automation. Unlike manufacturing, where robotic solutions benefit from the structured layout of the environment (e.g., factory assembly line), construction robots face unique challenges that arise from the rugged, dynamic, and unstructured environment of the work site, as well as the uncertainty and evolving sequence of occurring on-site events. This challenges any intended construction robots to not only replicate basic human motion, but also be capable of sensing and adapting to environmental changes, and making decisions based on the evolving state of the environment. Building upon recent advancements in robotic mapping, computer vision, and object recognition, the authors propose to introduce autonomous behavior at the basic task level for on-site construction robots to address these challenges in a flexible and extensible manner. This paper reports the outcome of the first phase of this research -a structured methodology for improved design and development of basic task automations -and focuses on algorithms developed for mobile robot navigation and relative pose estimation. The algorithms are implemented on a prototype mobile robotic platform, and evaluated in several experimental scenarios.

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“…Early efforts to use 3D-I laser technology for mobile robot navigation showed that although the system was capable of guiding a mobile robot [9], its use was restricted due to loss of track at relatively low vehicle speeds [10]. Upgrades to the positioning technology continued and a successful combination of indoor 2-D map creation and autonomous navigation was demonstrated in a research project at the Rochester Institute of Technology [11].…”

Section: Prior 3d-i / Mobile Robot Integrationmentioning

confidence: 99%

Development of a Robotic Structural Steel Placement System

Lytle

Saidi

Stone

2002

Proceedings of the 19th International Symposium on Automation and Robotics in Construction (ISARC)

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ABSTRACT:The NIST Construction Metrology and Automation Group, in cooperation with the NIST Intelligent Systems Division, is researching robotic structural steel placement as part of a project to develop an Automated Steel Construction Testbed. This project was initiated in response to industry requests for advanced tools and methodologies to speed the erection of steel structures while maintaining or enhancing standards for worker safety and facility reliability. This initial effort integrates and extends prior NIST research in robotic crane employment, teleoperated steel beam placement, laser-based site metrology, construction component tracking, and web-enabled 3-D visualization.

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Autonomous vehicle navigation with real-time 3D laser based positioning for construction

Cited by 28 publications

References 13 publications

BeAMS: A Beacon-Based Angle Measurement Sensor for Mobile Robot Positioning

BeAMS: A Beacon-Based Angle Measurement Sensor for Mobile Robot Positioning

Human-Robot Integration for Pose Estimation and Semi-Autonomous Navigation on Unstructured Construction Sites

Development of a Robotic Structural Steel Placement System

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