World feature detection and mapping using stereovision and inertial sensors

Lobo, Jorge; Queiroz, Carlos M.; Dias, Jorge

doi:10.1016/s0921-8890(03)00011-3

Cited by 18 publications

(10 citation statements)

References 38 publications

(30 reference statements)

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“…An overview of the machine vision technologies is given in [12]. Multiple of these technologies are also already described in use cases similar to the ones at the EnRicH 2017 [2]. Approaches the task with stereo vision and inertial measurements to determine the position of the robot and its surroundings.…”

Section: State Of the Artmentioning

confidence: 99%

Mobile Robot for Exploration and Manipulation Inside a Nuclear Power Plant

Ritzberger¹,

Emenshuber²,

Schubert³

et al. 2017

DAAAM Proceedings

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Section: State Of the Artmentioning

confidence: 99%

Mobile Robot for Exploration and Manipulation Inside a Nuclear Power Plant

Ritzberger¹,

Emenshuber²,

Schubert³

et al. 2017

DAAAM Proceedings

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“…Among all the existing sensory techniques that can be potentially used for mapping, stereovision is probably the most studied method [14]. A stereo camera is the prime example of a passive optical triangulation system.…”

Section: Stereovisionmentioning

confidence: 99%

A novel 3D sensory system for robot-assisted mapping of cluttered urban search and rescue environments

Zhang

Nejat

Guo

et al. 2010

Intel Serv Robotics

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In this paper, the first application of utilizing a unique 3D sensor for sequential 3D map building in unknown cluttered urban search and rescue (USAR) environments is proposed. The sensor utilizes a digital fringe projection and phase shifting technique to provide real-time 2D and 3D sensory information of the environment. The proposed sensor is unique over current technologies in that high-resolution 3D information of rubble filled environments can be acquired from the single sensor at a speed of 30 frames per second (fps). Furthermore, we propose the development of a novel robust and reliable landmark identification technique that utilizes both 2D and 3D depth images taken by the sensor for 3D mapping. Preliminary experiments show the potential of the real-time 3D sensory system and landmark identification scheme for robotic 3D mapping in unknown cluttered USAR-like environments.

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“…In ref. 4 world vertical feature detection and 3D mapping is presented. In this article we continue to explore the use of inertial data in vision systems, and present a method for fast alignment and segmentation of depth maps obtained from correlation based stereovision.…”

Section: • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •mentioning

confidence: 99%

Inertial Sensed Ego‐motion for 3D Vision

Lobo

Dias

2003

J. Robotic Syst.

Self Cite

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Inertial sensors attached to a camera can provide valuable data about camera pose and movement. In biological vision systems, inertial cues provided by the vestibular system are fused with vision at an early processing stage. In this article we set a framework for the combination of these two sensing modalities. Cameras can be seen as ray direction measuring devices, and in the case of stereo vision, depth along the ray can also be computed. The ego-motion can be sensed by the inertial sensors, but there are limitations determined by the sensor noise level. Keeping track of the vertical direction is required, so that gravity acceleration can be compensated for, and provides a valuable spatial reference. Results are shown of stereo depth map alignment using the vertical reference. The depth map points are mapped to a vertically aligned world frame of reference. In order to detect the ground plane, a histogram is performed for the different heights. Taking the ground plane as a reference plane for the acquired maps, the fusion of multiple maps reduces to a 2D translation and rotation problem. The dynamic inertial cues can be used as a first approximation for this transformation, allowing a fast depth map registration method. They also provide an image independent location of the image focus of expansion and center of rotation useful during visual based navigation tasks.

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World feature detection and mapping using stereovision and inertial sensors

Cited by 18 publications

References 38 publications

Mobile Robot for Exploration and Manipulation Inside a Nuclear Power Plant

Mobile Robot for Exploration and Manipulation Inside a Nuclear Power Plant

A novel 3D sensory system for robot-assisted mapping of cluttered urban search and rescue environments

Inertial Sensed Ego‐motion for 3D Vision

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