scholarly journals EVALUATING CONTINUOUS-TIME SLAM USING A PREDEFINED TRAJECTORY PROVIDED BY A ROBOTIC ARM

2017 ◽  
Vol IV-2/W4 ◽  
pp. 91-98
Author(s):  
B. Koch ◽  
R. Leblebici ◽  
A. Martell ◽  
S. Jörissen ◽  
K. Schilling ◽  
...  
Keyword(s):  
Continuous Time ◽  
Point Cloud ◽  
Degrees Of Freedom ◽  
Laser Scanner ◽  
Ground Truth ◽  
Robotic Arm ◽  
Laser Sensor ◽  
Test Environment ◽  
Previous State ◽  
Slam Algorithm

Recently published approaches to SLAM algorithms process laser sensor measurements and output a map as a point cloud of the environment. Often the actual precision of the map remains unclear, since SLAMalgorithms apply local improvements to the resulting map. Unfortunately, it is not trivial to compare the performance of SLAMalgorithms objectively, especially without an accurate ground truth. This paper presents a novel benchmarking technique that allows to compare a precise map generated with an accurate ground truth trajectory to a map with a manipulated trajectory which was distorted by different forms of noise. The accurate ground truth is acquired by mounting a laser scanner on an industrial robotic arm. The robotic arm is moved on a predefined path while the position and orientation of the end-effector tool are monitored. During this process the 2D profile measurements of the laser scanner are recorded in six degrees of freedom and afterwards used to generate a precise point cloud of the test environment. For benchmarking, an offline continuous-time SLAM algorithm is subsequently applied to remove the inserted distortions. Finally, it is shown that the manipulated point cloud is reversible to its previous state and is slightly improved compared to the original version, since small errors that came into account by imprecise assumptions, sensor noise and calibration errors are removed as well.

scholarly journals A comparison of multi-view 3D reconstruction of a rock wall using several cameras and a laser scanner

2014 ◽  
Vol XL-5 ◽  
pp. 573-580 ◽  
Author(s):  
K. Thoeni ◽  
A. Giacomini ◽  
R. Murtagh ◽  
E. Kniest
Keyword(s):  
3D Reconstruction ◽  
Point Cloud ◽  
Laser Scanner ◽  
Ground Truth ◽  
Point Clouds ◽  
Digital Cameras ◽  
Rock Wall ◽  
Geological Features ◽  
Dense Point ◽  
Sharp Edges

This work presents a comparative study between multi-view 3D reconstruction using various digital cameras and a terrestrial laser scanner (TLS). Five different digital cameras were used in order to estimate the limits related to the camera type and to establish the minimum camera requirements to obtain comparable results to the ones of the TLS. The cameras used for this study range from commercial grade to professional grade and included a GoPro Hero 1080 (5 Mp), iPhone 4S (8 Mp), Panasonic Lumix LX5 (9.5 Mp), Panasonic Lumix ZS20 (14.1 Mp) and Canon EOS 7D (18 Mp). The TLS used for this work was a FARO Focus 3D laser scanner with a range accuracy of ±2 mm. The study area is a small rock wall of about 6 m height and 20 m length. The wall is partly smooth with some evident geological features, such as non-persistent joints and sharp edges. Eight control points were placed on the wall and their coordinates were measured by using a total station. These coordinates were then used to georeference all models. A similar number of images was acquired from a distance of between approximately 5 to 10 m, depending on field of view of each camera. The commercial software package PhotoScan was used to process the images, georeference and scale the models, and to generate the dense point clouds. Finally, the open-source package CloudCompare was used to assess the accuracy of the multi-view results. Each point cloud obtained from a specific camera was compared to the point cloud obtained with the TLS. The latter is taken as ground truth. The result is a coloured point cloud for each camera showing the deviation in relation to the TLS data. The main goal of this study is to quantify the quality of the multi-view 3D reconstruction results obtained with various cameras as objectively as possible and to evaluate its applicability to geotechnical problems.

Integrating laser profile sensor to an industrial robotic arm for improving quality inspection in manufacturing processes

2020 ◽  
pp. 095440622094255
Author(s):  
Toufik Al Khawli ◽  
Muddasar Anwar ◽  
Dongming Gan ◽  
Shafiqul Islam
Keyword(s):  
Degrees Of Freedom ◽  
Ground Truth ◽  
Calibration Procedure ◽  
Robotic Arm ◽  
Manufacturing Processes ◽  
Quality Inspection ◽  
Six Degrees Of Freedom ◽  
Tool Positioning ◽  
Sharp Object ◽  
Laser Profile

This paper investigates the integration of laser profile sensor to an industrial robotic arm for automating the quality inspection in manufacturing processes that requires a manual labour intensive work. The aim was to register the measurements from a laser profile sensor mounted on a six degrees-of-freedom robot with respect to the robot base frame. The registration is based on a six degrees-of-freedom calibration, which is an essential step for several automated manufacturing processes that require high level of accuracy in tool positioning and alignment on one hand, and quality inspection systems that require flexibility and accurate measurements on the other hand. The investigation compromises of two calibration procedures namely the calibration using a sharp object and the planar constraints. The solution of the calibration procedures estimated from both iterative and optimization solvers is thoroughly discussed. By implementing a simulation platform that generates virtual data for the two procedures with additional levels of noise, the six-dimensional poses are estimated and compared to the ground truth. Finally, an experimental test using a laser profile from Acuity mounted on Mitsubishi RV-6SDL manipulator is presented to investigate the measurement accuracy with four estimated laser poses. The calibration procedure using a sharp object shows the most accurate simulation and experimental results under the effect of noise.

scholarly journals SIMULTANEOUS LOCALIZATION AND MAPPING FOR SEMI-SPARSE POINT CLOUDS

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 1009-1014
Author(s):  
P. Shokrzadeh
Keyword(s):  
Point Cloud ◽  
Laser Scanner ◽  
Simultaneous Localization And Mapping ◽  
Point Clouds ◽  
Coordinate Frame ◽  
Localization And Mapping ◽  
Engineering Sciences ◽  
Outdoor Environments ◽  
Slam Algorithm ◽  
Short Time

Abstract. 3D representation of the environment is a piece of vital information for most of the engineering sciences. However, providing such information in classical surveying approaches demands a considerable amount of time for localizing the sensor in a desired coordinate frame to map the environment. Simultaneous Localization And Mapping (SLAM) algorithm is capable of localizing the sensor and do the mapping while the sensor is moving through the environment. In this paper, SLAM will be applied on the data of a lightweight 3D laser scanner in which we call semi-sparse point cloud, because of the unique specifications of the point cloud which comes from various resolutions in vertical and horizontal directions. In contrast to most of the SLAM algorithms, there is no aiding sensor to provide prior information of motion. The output of the algorithm would be a high-density full geometry detailed map in a short time. The accuracy of the algorithm has been estimated in a medium scale simulated outdoor environments in Gazebo and Robot Operating System (ROS). Considering Velodyne Puck accuracy which is 3 cm, the map was generated with approximately 6 cm accuracy.

scholarly journals COST EFFECTIVE SPHERICAL PHOTOGRAMMETRY: A NOVEL FRAMEWORK FOR THE SMART MANAGEMENT OF COMPLEX URBAN ENVIRONMENTS

2020 ◽  
Vol XLIII-B4-2020 ◽  
pp. 441-448
Author(s):  
S. Chiappini ◽  
A. Fini ◽  
E. S. Malinverni ◽  
E. Frontoni ◽  
G. Racioppi ◽  
...  
Keyword(s):  
Point Cloud ◽  
Low Cost ◽  
Laser Scanner ◽  
Ground Truth ◽  
Cost Effective ◽  
Data Retrieval ◽  
Acquisition Time ◽  
Cloud Data ◽  
Tax Assessment ◽  
Final Goal

Abstract. The development and urban planning of a modern city, nowadays, should be entrusted on the implementation of methods and techniques which require a management of complex information. The final goal is to support local authorities for the decision making. Finding data that are often heterogeneous but nevertheless connected to each other is useful to create a virtuous management model based on an empirical and objective study system. It will therefore be important to develop a system of data retrieval, analysis and management as accurate as possible, usable by all the actors involved in the governance of the territories. The article focuses on the implementation of an effective workflow for the management of complex urban data, the final goal of such framework, is the creation of a Smart City 3D Platform capable of providing innovative services for tax assessment and collection. In particular, it investigates over the potential of using spherical photogrammetry, to guarantee fast, low-cost and reliable acquisition time. The resulting 3D model has been then georeferenced with GNSS coordinates to ensure the desired precision, while the assessment of the model has been done using laser scanner data as a ground truth. The point cloud obtained from the processing can be managed and edited in a WEBGIS, which merges 2D (cadastral register) and 3D (point cloud) data. The project is the result of the collaboration between the Università Politecnica delle Marche and the Company Andreani Tributi srl, with the aim of collecting information about the advertising structures present in the city of Brescia (Italy) for tax assessment.

scholarly journals IMPROVING GOOGLE'S CARTOGRAPHER 3D MAPPING BY CONTINUOUS-TIME SLAM

2017 ◽  
Vol XLII-2/W3 ◽  
pp. 543-549 ◽  
Author(s):  
A. Nüchter ◽  
M. Bleier ◽  
J. Schauer ◽  
P. Janotta
Keyword(s):  
Continuous Time ◽  
Point Cloud ◽  
Point Clouds ◽  
3D Mapping ◽  
3D Point Clouds ◽  
Slam Algorithm

This paper shows how to use the result of Google's SLAM solution, called Cartographer, to bootstrap our continuous-time SLAM algorithm. The presented approach optimizes the consistency of the global point cloud, and thus improves on Google’s results. We use the algorithms and data from Google as input for our continuous-time SLAM software. We also successfully applied our software to a similar backpack system which delivers consistent 3D point clouds even in absence of an IMU.

scholarly journals TIMESTAMP OFFSET DETERMINATION BETWEEN AN ACTUATED LASER SCANNER AND ITS CORRESPONDING MOTOR

2017 ◽  
Vol IV-1/W1 ◽  
pp. 99-106 ◽  
Author(s):  
R. Voges ◽  
C. S. Wieghardt ◽  
B. Wagner
Keyword(s):  
Data Acquisition ◽  
Point Cloud ◽  
Dimensional Space ◽  
Low Cost ◽  
Three Dimensional ◽  
Laser Scanner ◽  
3D Data ◽  
Laser Scanners ◽  
Slam Algorithm ◽  
Three Dimensional Space

Motor actuated 2D laser scanners are key sensors for many robotics applications that need wide ranging but low cost 3D data. There exist many approaches on how to build a 3D laser scanner using this technique, but they often lack proper synchronization for the timestamps of the actuator and the laser scanner. However, to transform the measurement points into three-dimensional space an appropriate synchronization is mandatory. Thus, we propose two different approaches to accomplish the goal of calculating timestamp offsets between laser scanner and motor prior to and after data acquisition. Both approaches use parts of a SLAM algorithm but apply different criteria to find an appropriate solution. While the approach for offset calculation prior to data acquisition exploits the fact that the SLAM algorithm should not register motion for a stationary system, the approach for offset calculation after data acquisition evaluates the perceived clarity of a point cloud created by the SLAM algorithm. Our experiments show that both approaches yield the same results although operating independently on different data, which demonstrates that the results reflect reality with a high probability. Furthermore, our experiments exhibit the significance of a proper synchronization between laser scanner and actuator.

scholarly journals An Open-Source Test Environment for Effective Development of MARG-Based Algorithms

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1183
Author(s):  
Ákos Odry
Keyword(s):  
Open Source ◽  
Degrees Of Freedom ◽  
Angular Rate ◽  
Three Dimensional ◽  
Ground Truth ◽  
Sensor Data ◽  
Test Environment ◽  
Estimation Algorithms ◽  
Test Platform ◽  
Effective Development

This paper presents an open-source environment for development, tuning, and performance evaluation of magnetic, angular rate, and gravity-based (MARG-based) filters, such as pose estimators and classification algorithms. The environment is available in both ROS/Gazebo and MATLAB/Simulink, and it contains a six-degrees of freedom (6 DOF) test bench, which simultaneously moves and rotates an MARG unit in the three-dimensional (3D) space. As the quality of MARG-based estimation becomes crucial in dynamic situations, the proposed test platform intends to simulate different accelerating and vibrating circumstances, along with realistic magnetic perturbation events. Moreover, the simultaneous acquisition of both the real pose states (ground truth) and raw sensor data is supported during these simulated system behaviors. As a result, the test environment executes the desired mixture of static and dynamic system conditions, and the provided database fosters the effective analysis of sensor fusion algorithms. The paper systematically describes the structure of the proposed test platform, from mechanical properties, over mathematical modeling and joint controller synthesis, to implementation results. Additionally, a case study is presented of the tuning of popular attitude estimation algorithms to highlight the advantages of the developed open-source environment.

scholarly journals A Vision-Based Sensing Approach for a Spherical Soft Robotic Arm

2021 ◽  
Vol 8 ◽  
Author(s):  
Matthias Hofer ◽  
Carmelo Sferrazza ◽  
Raffaello D’Andrea
Keyword(s):  
Motion Capture ◽  
Network Architecture ◽  
Degrees Of Freedom ◽  
Sensory Feedback ◽  
Ground Truth ◽  
Robotic Systems ◽  
Robotic Arm ◽  
Ground Truth Data ◽  
Rotational Degrees Of Freedom ◽  
Soft Robotic Arm

Sensory feedback is essential for the control of soft robotic systems and to enable deployment in a variety of different tasks. Proprioception refers to sensing the robot’s own state and is of crucial importance in order to deploy soft robotic systems outside of laboratory environments, i.e. where no external sensing, such as motion capture systems, is available. A vision-based sensing approach for a soft robotic arm made from fabric is presented, leveraging the high-resolution sensory feedback provided by cameras. No mechanical interaction between the sensor and the soft structure is required and consequently the compliance of the soft system is preserved. The integration of a camera into an inflatable, fabric-based bellow actuator is discussed. Three actuators, each featuring an integrated camera, are used to control the spherical robotic arm and simultaneously provide sensory feedback of the two rotational degrees of freedom. A convolutional neural network architecture predicts the two angles describing the robot’s orientation from the camera images. Ground truth data is provided by a motion capture system during the training phase of the supervised learning approach and its evaluation thereafter. The camera-based sensing approach is able to provide estimates of the orientation in real-time with an accuracy of about one degree. The reliability of the sensing approach is demonstrated by using the sensory feedback to control the orientation of the robotic arm in closed-loop.

The Development of a Myoelectric Training Tool for Above-Elbow Amputees

2012 ◽  
Vol 6 (1) ◽  
pp. 5-15 ◽  
Author(s):  
Michael R Dawson ◽  
Farbod Fahimi ◽  
Jason P Carey
Keyword(s):  
Degrees Of Freedom ◽  
Learning Task ◽  
Robotic Arm ◽  
Signal Acquisition ◽  
Myoelectric Prosthesis ◽  
Training Tool ◽  
Myoelectric Prostheses ◽  
Training Systems ◽  
Targeted Muscle Reinnervation

The objective of above-elbow myoelectric prostheses is to reestablish the functionality of missing limbs and increase the quality of life of amputees. By using electromyography (EMG) electrodes attached to the surface of the skin, amputees are able to control motors in myoelectric prostheses by voluntarily contracting the muscles of their residual limb. This work describes the development of an inexpensive myoelectric training tool (MTT) designed to help upper limb amputees learn how to use myoelectric technology in advance of receiving their actual myoelectric prosthesis. The training tool consists of a physical and simulated robotic arm, signal acquisition hardware, controller software, and a graphical user interface. The MTT improves over earlier training systems by allowing a targeted muscle reinnervation (TMR) patient to control up to two degrees of freedom simultaneously. The training tool has also been designed to function as a research prototype for novel myoelectric controllers. A preliminary experiment was performed in order to evaluate the effectiveness of the MTT as a learning tool and to identify any issues with the system. Five able-bodied participants performed a motor-learning task using the EMG controlled robotic arm with the goal of moving five balls from one box to another as quickly as possible. The results indicate that the subjects improved their skill in myoelectric control over the course of the trials. A usability survey was administered to the subjects after their trials. Results from the survey showed that the shoulder degree of freedom was the most difficult to control.

Handheld Laser Scanner Research

2019 ◽  
Vol 952 (10) ◽  
pp. 47-54
Author(s):  
A.V. Komissarov ◽  
A.V. Remizov ◽  
M.M. Shlyakhova ◽  
K.K. Yambaev
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Test Site ◽  
Optical Systems ◽  
Advantages And Disadvantages ◽  
Site Survey ◽  
Laser Scanners ◽  
Three Dimensional Models ◽  
The Stability

The authors consider hand-held laser scanners, as a new photogrammetric tool for obtaining three-dimensional models of objects. The principle of their work and the newest optical systems based on various sensors measuring the depth of space are described in detail. The method of simultaneous navigation and mapping (SLAM) used for combining single scans into point cloud is outlined. The formulated tasks and methods for performing studies of the DotProduct (USA) hand-held laser scanner DPI?8X based on a test site survey are presented. The accuracy requirements for determining the coordinates of polygon points are given. The essence of the performed experimental research of the DPI?8X scanner is described, including scanning of a test object at various scanner distances, shooting a test polygon from various scanner positions and building point cloud, repeatedly shooting the same area of the polygon to check the stability of the scanner. The data on the assessment of accuracy and analysis of research results are given. Fields of applying hand-held laser scanners, their advantages and disadvantages are identified.

Sign in / Sign up

Export Citation Format

Share Document