Real-Time Tree Foliage Estimation Using a Ground Laser Scanner

2006 ◽  
Author(s):  
J. Palacin
Keyword(s):  
Real Time ◽  
Laser Scanner ◽  
Tree Foliage

scholarly journals Real-Time Tree Foliage Estimation Using a Ground Laser Scanner

2006 ◽  
Author(s):  
J. Palacin ◽  
J.A. Salse ◽  
R. Sanz ◽  
M. Ribes-Dasi ◽  
J. Masip ◽  
...  
Keyword(s):  
Real Time ◽  
Laser Scanner ◽  
Tree Foliage

scholarly journals Real-Time Tree-Foliage Surface Estimation Using a Ground Laser Scanner

2007 ◽  
Vol 56 (4) ◽  
pp. 1377-1383 ◽  
Author(s):  
Jordi Palacin ◽  
Tomas Palleja ◽  
Marcel Tresanchez ◽  
Ricardo Sanz ◽  
Jordi Llorens ◽  
...  
Keyword(s):  
Real Time ◽  
Laser Scanner ◽  
Surface Estimation ◽  
Tree Foliage

scholarly journals Assessment of the Accuracy of a Multi-Beam LED Scanner Sensor for Measuring Olive Canopies

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4406 ◽  
Author(s):  
Rafael Sola-Guirado ◽  
Sergio Bayano-Tejero ◽  
Antonio Rodríguez-Lizana ◽  
Jesús Gil-Ribes ◽  
Antonio Miranda-Fuentes
Keyword(s):  
Laboratory Test ◽  
Real Time ◽  
Relative Error ◽  
Laser Scanner ◽  
Field Tests ◽  
High Accuracy ◽  
Field Conditions ◽  
Canopy Trees ◽  
Canopy Volume

Canopy characterization has become important when trying to optimize any kind of agricultural operation in high-growing crops, such as olive. Many sensors and techniques have reported satisfactory results in these approaches and in this work a 2D laser scanner was explored for measuring canopy trees in real-time conditions. The sensor was tested in both laboratory and field conditions to check its accuracy, its cone width, and its ability to characterize olive canopies in situ. The sensor was mounted on a mast and tested in laboratory conditions to check: (i) its accuracy at different measurement distances; (ii) its measurement cone width with different reflectivity targets; and (iii) the influence of the target’s density on its accuracy. The field tests involved both isolated and hedgerow orchards, in which the measurements were taken manually and with the sensor. The canopy volume was estimated with a methodology consisting of revolving or extruding the canopy contour. The sensor showed high accuracy in the laboratory test, except for the measurements performed at 1.0 m distance, with 60 mm error (6%). Otherwise, error remained below 20 mm (1% relative error). The cone width depended on the target reflectivity. The accuracy decreased with the target density.

scholarly journals A Clustering Framework for Real-time Rendering of Tree Foliage

2007 ◽  
Vol 2 (4) ◽  
Author(s):  
Cristina Rebollo ◽  
Inmaculada Remolar ◽  
Miguel Chover ◽  
Jesús Gumbau ◽  
Oscar Ripollés
Keyword(s):  
Real Time ◽  
Tree Foliage

A new real-time shape acquisition with a laser scanner: first test results

2010 ◽  
Vol 26 (6) ◽  
pp. 543-550 ◽  
Author(s):  
Vincenzo Niola ◽  
Cesare Rossi ◽  
Sergio Savino
Keyword(s):  
Real Time ◽  
Laser Scanner ◽  
Test Results ◽  
Shape Acquisition ◽  
Time Shape

scholarly journals MOVING OBJECT CLASSIFICATION USING MULTILAYER LASER SCANNING WITH SPACE SUBDIVISION FRAMEWORK

2020 ◽  
Vol V-4-2020 ◽  
pp. 103-108
Author(s):  
M. Nakagawa ◽  
M. Taguchi
Keyword(s):  
Real Time ◽  
Urban Areas ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Object Classification ◽  
Point Clouds ◽  
Satellite System ◽  
Space Subdivision ◽  
Position Data ◽  
Global Navigation Satellite

Abstract. In this paper, we focus on the development of intelligent construction vehicles to improve the safety of workers in construction sites. Generally, global navigation satellite system positioning is utilized to obtain the position data of workers and construction vehicles. However, construction fields in urban areas have poor satellite positioning environments. Therefore, we have developed a 3D sensing unit mounted on a construction vehicle for worker position data acquisition. The unit mainly consists of a multilayer laser scanner. We propose a real-time object measurement, classification and tracking methodology with the multilayer laser scanner. We also propose a methodology to estimate and visualize object behaviors with a spatial model based on a space subdivision framework consisting of agents, activities, resources, and modifiers. We applied the space subdivision framework with a geofencing approach using real-time object classification and tracking results estimated from temporal point clouds. Our methodology was evaluated using temporal point clouds acquired from a construction vehicle in drilling works.

scholarly journals Remote Indoor Construction Progress Monitoring Using Extended Reality

2020 ◽  
Author(s):  
Ahmed Khairadeen Ali ◽  
One Jae Lee ◽  
DoYeop Lee ◽  
Chansik Park
Keyword(s):  
Real Time ◽  
Data Exchange ◽  
Progress Monitoring ◽  
Laser Scanner ◽  
Visual Programming ◽  
Inspection System ◽  
Cloud Data ◽  
Recent Developments ◽  
Scan Data ◽  
Processing And Storage

Despite recent developments in monitoring and visualizing construction progress, the data exchange between construction jobsite and office lacks automation and real-time recording. To address this issue, a near real-time construction work inspection system called iVR is proposed; this system integrates 3D scanning, extended reality, and visual programming to visualize interactive onsite inspection for indoor activities and provide numeric data. iVR comprises five modules: iVR-location finder (finding laser scanner located in the construction site) iVR-scan (capture point cloud data of jobsite indoor activity), iVR-prepare (processes and convert 3D scan data into a 3D model), iVR-inspect (conduct immersive visual reality inspection in construction office), and iVR-feedback (visualize inspection feedback from jobsite using augmented reality). An experimental lab test is conducted to validate the applicability of iVR process; it successfully exchanges required information between construction jobsite and office in a specific time. This system is expected to assist Engineers and workers in quality assessment, progress assessments, and decision-making which can realize a productive and practical communication platform, unlike conventional monitoring or data capturing, processing, and storage methods, which involve storage, compatibility, and time-consumption issues.

Autonomous Mobile Robot Searching for Persons with Specific Clothing on Urban Walkway

2017 ◽  
Vol 29 (4) ◽  
pp. 649-659 ◽  
Author(s):  
Ryohsuke Mitsudome ◽  
◽  
Hisashi Date ◽  
Azumi Suzuki ◽  
Takashi Tsubouchi ◽  
...  
Keyword(s):  
Object Recognition ◽  
Mobile Robot ◽  
Real Time ◽  
Real World ◽  
Laser Scanner ◽  
High Accuracy ◽  
Autonomous Mobile Robot ◽  
World Environment

In order for a robot to provide service in a real world environment, it has to navigate safely and recognize the surroundings. We have participated in Tsukuba Challenge to develop a robot with robust navigation and accurate object recognition capabilities. To achieve navigation, we have introduced the ROS packages, and the robot was able to navigate without major collisions throughout the challenge. For object recognition, we used both a laser scanner and camera to recognize a person in specific clothing, in real time and with high accuracy. In this paper, we evaluate the accuracy of recognition and discuss how it can be improved.

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