scholarly journals Autonomous Navigation of a Center-Articulated and Hydrostatic Transmission Rover using a Modified Pure Pursuit Algorithm in a Cotton Field

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4412
Author(s):  
Kadeghe Fue ◽  
Wesley Porter ◽  
Edward Barnes ◽  
Changying Li ◽  
Glen Rains
Keyword(s):  
Autonomous Navigation ◽  
Low Cost ◽  
Path Following ◽  
Absolute Error ◽  
Satellite System ◽  
Measurement Unit ◽  
Cotton Field ◽  
Cotton Production ◽  
Hydrostatic Transmission ◽  
Pure Pursuit

This study proposes an algorithm that controls an autonomous, multi-purpose, center-articulated hydrostatic transmission rover to navigate along crop rows. This multi-purpose rover (MPR) is being developed to harvest undefoliated cotton to expand the harvest window to up to 50 days. The rover would harvest cotton in teams by performing several passes as the bolls become ready to harvest. We propose that a small robot could make cotton production more profitable for farmers and more accessible to owners of smaller plots of land who cannot afford large tractors and harvesting equipment. The rover was localized with a low-cost Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS), encoders, and Inertial Measurement Unit (IMU)s for heading. Robot Operating System (ROS)-based software was developed to harness the sensor information, localize the rover, and execute path following controls. To test the localization and modified pure-pursuit path-following controls, first, GNSS waypoints were obtained by manually steering the rover over the rows followed by the rover autonomously driving over the rows. The results showed that the robot achieved a mean absolute error (MAE) of 0.04 m, 0.06 m, and 0.09 m for the first, second and third passes of the experiment, respectively. The robot achieved an MAE of 0.06 m. When turning at the end of the row, the MAE from the RTK-GNSS-generated path was 0.24 m. The turning errors were acceptable for the open field at the end of the row. Errors while driving down the row did damage the plants by moving close to the plants’ stems, and these errors likely would not impede operations designed for the MPR. Therefore, the designed rover and control algorithms are good and can be used for cotton harvesting operations.

scholarly journals Stereo Visual Odometry for Indoor Localization of Ship Model

2020 ◽  
Vol 58 (1) ◽  
pp. 57-75
Author(s):  
Mario Kučić ◽  
Marko Valčić
Keyword(s):  
Autonomous Navigation ◽  
Inertial Measurement Unit ◽  
Indoor Localization ◽  
Low Cost ◽  
Visual Odometry ◽  
Measurement Unit ◽  
Ship Model ◽  
Open Sea ◽  
Autonomous Cars ◽  
Stereo Cameras

Typically, ships are designed for open sea navigation and thus research of autonomous ships is mostly done for that particular area. This paper explores the possibility of using low-cost sensors for localization inside the small navigation area. The localization system is based on the technology used for developing autonomous cars. The main part of the system is visual odometry using stereo cameras fused with Inertial Measurement Unit (IMU) data coupled with Kalman and particle filters to get decimetre level accuracy inside a basin for different surface conditions. The visual odometry uses cropped frames for stereo cameras and Good features to track algorithm for extracting features to get depths for each feature that is used for estimation of ship model movement. Experimental results showed that the proposed system could localize itself within a decimetre accuracy implying that there is a real possibility for ships in using visual odometry for autonomous navigation on narrow waterways, which can have a significant impact on future transportation.

scholarly journals Assessment of the Steering Precision of a Hydrographic USV along Sounding Profiles Using a High-Precision GNSS RTK Receiver Supported Autopilot

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5637
Author(s):  
Łukasz Marchel ◽  
Cezary Specht ◽  
Mariusz Specht
Keyword(s):  
High Precision ◽  
Low Cost ◽  
Path Following ◽  
Satellite System ◽  
Magnetic Compass ◽  
Reference Station ◽  
Positioning System ◽  
Positioning Accuracy ◽  
Unmanned Surface Vehicles ◽  
Global Navigation Satellite

Unmanned Surface Vehicles (USV) are increasingly used to perform numerous tasks connected with measurements in inland waters and seas. One of such target applications is hydrography, where traditional (manned) bathymetric measurements are increasingly often realized by unmanned surface vehicles. This pertains especially to restricted or hardly navigable waters, in which execution of hydrographic surveys with the use of USVs requires precise maneuvering. Bathymetric measurements should be realized in a way that makes it possible to determine the waterbody’s depth as precisely as possible, and this requires high-precision in navigating along planned sounding profiles. This paper presents research that aimed to determine the accuracy of unmanned surface vehicle steering in autonomous mode (with a Proportional-Integral-Derivative (PID) controller) along planned hydrographic profiles. During the measurements, a high-precision Global Navigation Satellite System (GNSS) Real Time Kinematic (RTK) positioning system based on a GNSS reference station network (positioning accuracy: 1–2 cm, p = 0.95) and a magnetic compass with the stability of course maintenance of 1°–3° Root Mean Square (RMS) were used. For the purpose of evaluating the accuracy of the vessel’s path following along sounding profiles, the cross track error (XTE) measure, i.e., the distance between an USV’s position and the hydrographic profile, calculated transversely to the course, was proposed. The tests were compared with earlier measurements taken by other unmanned surface vehicles, which followed the exact same profiles with the use of much simpler and low-cost multi-GNSS receiver (positioning accuracy: 2–2.5 m or better, p = 0.50), supported with a Fluxgate magnetic compass with a high course measurement accuracy of 0.3° (p = 0.50 at 30 m/s). The research has shown that despite the considerable difference in the positioning accuracy of both devices and incomparably different costs of both solutions, the authors proved that the use of the GNSS RTK positioning system, as opposed to a multi-GNSS system supported with a Fluxgate magnetic compass, influences the precision of USV following sounding profiles to an insignificant extent.

USV attitude estimation: an approach using quaternion in direction cosine matrix

Robotica ◽  
2014 ◽  
Vol 34 (5) ◽  
pp. 995-1009 ◽  
Author(s):  
Chiemela Onunka ◽  
Glen Bright ◽  
Riaan Stopforth
Keyword(s):  
Global Positioning System ◽  
Autonomous Navigation ◽  
Low Cost ◽  
Direction Cosine ◽  
Attitude Estimation ◽  
Measurement Unit ◽  
Advanced Technique ◽  
Navigation Data ◽  
Global Positioning ◽  
Direction Cosine Matrix

SUMMARYPositioning and navigation data for unmanned surface vehicles (USVs) are extracted using the Global Positioning System (GPS) and the Inertial Navigation System (INS) integrated with an inertial measurement unit (IMU). The integration of quaternion with direction cosine matrix (DCM) with the aim of obtaining high accuracy with complete system independence has been effectively used to supply position and attitude information for autonomous navigation of marine crafts. A DCM integrated with a quaternion provided an advanced technique for precise USV attitude estimation and position determination using low-cost sensors. This paper presents the implementation of an INS developed by the integration of DCM and quaternion.

scholarly journals Performance Analysis of Network-RTK Techniques for Drone Navigation considering Ionospheric Conditions

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Tae-Suk Bae ◽  
Minho Kim
Keyword(s):  
Autonomous Navigation ◽  
Low Cost ◽  
Satellite System ◽  
Test Results ◽  
Static Mode ◽  
Fixed Integer ◽  
Gnss Receivers ◽  
Global Navigation Satellite ◽  
Ionospheric Condition ◽  
Mapping Purpose

Recently, an accurate positioning has become the kernel of autonomous navigation with the rapid growth of drones including mapping purpose. The Network-based Real-time Kinematic (NRTK) system was predominantly used for precision positioning in many fields such as surveying and agriculture, mostly in static mode or low-speed operation. The NRTK positioning, in general, shows much better performance with the fixed integer ambiguities. However, the success rate of the ambiguity resolution is highly dependent on the ionospheric condition and the surrounding environment of Global Navigation Satellite System (GNSS) positioning, which particularly corresponds to the low-cost GNSS receivers. We analyzed the effects of the ionospheric conditions on the GNSS NRTK, as well as the possibility of applying the mobile NRTK to drone navigation for mapping. Two NRTK systems in operation were analyzed during a period of high ionospheric conditions, and the accuracy and the performance were compared for several operational cases. The test results show that a submeter accuracy is available even with float ambiguity under a favorable condition (i.e., visibility of the satellites as well as stable ionosphere). We still need to consider how to deal with ionospheric disturbances which may prevent NRTK positioning.

Path Following for the Soft Origami Crawling Robot

2019 ◽  
Author(s):  
Oyuna Angatkina ◽  
Kimberly Gustafson ◽  
Aimy Wissa ◽  
Andrew Alleyne
Keyword(s):  
Autonomous Navigation ◽  
Degrees Of Freedom ◽  
Kinematic Model ◽  
Path Following ◽  
Search And Rescue ◽  
Soft Robots ◽  
Path Following Control ◽  
Straight Line ◽  
Pure Pursuit ◽  
Extensive Growth

Abstract Extensive growth of the soft robotics field has made possible the application of soft mobile robots for real world tasks such as search and rescue missions. Soft robots provide safer interactions with humans when compared to traditional rigid robots. Additionally, soft robots often contain more degrees of freedom than rigid ones, which can be beneficial for applications where increased mobility is needed. However, the limited number of studies for the autonomous navigation of soft robots currently restricts their application for missions such as search and rescue. This paper presents a path following technique for a compliant origami crawling robot. The path following control adapts the well-known pure pursuit method to account for the geometric and mobility constraints of the robot. The robot motion is described by a kinematic model that transforms the outputs of the pure pursuit into the servo input rotations for the robot. This model consists of two integrated sub-models: a lumped kinematic model and a segmented kinematic model. The performance of the path following approach is demonstrated for a straight-line following simulation with initial offset. Finally, a feedback controller is designed to account for terrain or mission uncertainties.

scholarly journals Prediction of Cow Calving in Extensive Livestock Using a New Neck-Mounted Sensorized Wearable Device: A Pilot Study

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8060
Author(s):  
Carlos González-Sánchez ◽  
Guillermo Sánchez-Brizuela ◽  
Ana Cisnal ◽  
Juan-Carlos Fraile ◽  
Javier Pérez-Turiel ◽  
...  
Keyword(s):  
Low Cost ◽  
Satellite System ◽  
Wearable Device ◽  
Measurement Unit ◽  
Time Data ◽  
Livestock Farming ◽  
Preliminary Study ◽  
Real Time Data Processing ◽  
Global Navigation Satellite ◽  
Computational Resources

In this study, new low-cost neck-mounted sensorized wearable device is presented to help farmers detect the onset of calving in extensive livestock farming by continuously monitoring cow data. The device incorporates three sensors: an inertial measurement unit (IMU), a global navigation satellite system (GNSS) receiver, and a thermometer. The hypothesis of this study was that onset calving is detectable through the analyses of the number of transitions between lying and standing of the animal (lying bouts). A new algorithm was developed to detect calving, analysing the frequency and duration of lying and standing postures. An important novelty is that the proposed algorithm has been designed with the aim of being executed in the embedded microcontroller housed in the cow’s collar and, therefore, it requires minimal computational resources while allowing for real time data processing. In this preliminary study, six cows were monitored during different stages of gestation (before, during, and after calving), both with the sensorized wearable device and by human observers. It was carried out on an extensive livestock farm in Salamanca (Spain), during the period from August 2020 to July 2021. The preliminary results obtained indicate that lying-standing animal states and transitions may be useful to predict calving. Further research, with data obtained in future calving of cows, is required to refine the algorithm.

scholarly journals ACCURATE ESTIMATION OF ORIENTATION PARAMETERS OF UAV IMAGES THROUGH IMAGE REGISTRATION WITH AERIAL OBLIQUE IMAGERY

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 599-605 ◽  
Author(s):  
F. A. Onyango ◽  
F. Nex ◽  
M. S. Peter ◽  
P. Jende
Keyword(s):  
Low Cost ◽  
Satellite System ◽  
Aerial Images ◽  
Measurement Unit ◽  
Accurate Estimation ◽  
Ratio Test ◽  
Uav Images ◽  
Global Navigation Satellite ◽  
The Impact ◽  
Orientation Parameters

Unmanned Aerial Vehicles (UAVs) have gained popularity in acquiring geotagged, low cost and high resolution images. However, the images acquired by UAV-borne cameras often have poor georeferencing information, because of the low quality on-board Global Navigation Satellite System (GNSS) receiver. In addition, lightweight UAVs have a limited payload capacity to host a high quality on-board Inertial Measurement Unit (IMU). Thus, orientation parameters of images acquired by UAV-borne cameras may not be very accurate.<br><br> Poorly georeferenced UAV images can be correctly oriented using accurately oriented airborne images capturing a similar scene by finding correspondences between the images. This is not a trivial task considering the image pairs have huge variations in scale, perspective and illumination conditions. This paper presents a procedure to successfully register UAV and aerial oblique imagery. The proposed procedure implements the use of the AKAZE interest operator for feature extraction in both images. Brute force is implemented to find putative correspondences and later on Lowe’s ratio test (Lowe, 2004) is used to discard a significant number of wrong matches. In order to filter out the remaining mismatches, the putative correspondences are used in the computation of multiple homographies, which aid in the reduction of outliers significantly. In order to increase the number and improve the quality of correspondences, the impact of pre-processing the images using the Wallis filter (Wallis, 1974) is investigated. This paper presents the test results of different scenarios and the respective accuracies compared to a manual registration of the finally computed fundamental and essential matrices that encode the orientation parameters of the UAV images with respect to the aerial images.

scholarly journals A LIGHTWEIGHT UAV-BASED LASER SCANNING SYSTEM FOR FOREST APPLICATION

2018 ◽  
Vol 24 (3) ◽  
pp. 318-334 ◽  
Author(s):  
Fernanda Magri Torres ◽  
Antonio Maria Garcia Tommaselli
Keyword(s):  
Laser Scanning ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Temporal Frequency ◽  
Laser Scanner ◽  
Satellite System ◽  
Measurement Unit ◽  
Raspberry Pi ◽  
Scanning System ◽  
Point Density

Abstract Lightweight Unmanned Aerial Vehicles (UAVs) have become a cost effective alternative for studies which use aerial Remote Sensing with high temporal frequency requirements for small areas. Laser scanner devices are widely used for rapid tridimensional data acquisition, mainly as a complementary data source to photogrammetric surveying. Recent studies using laser scanner systems onboard UAVs for forestry inventory and mapping applications have presented encouraging results. This work describes the development and accuracy assessment of a low cost mapping platform composed by an Ibeo Lux scanner, a GNSS (Global Navigation Satellite System) antenna, an Inertial Navigation System Novatel Span-IGM-S1, integrating a GNSS receiver and an IMU (Inertial Measurement Unit), a Raspberry PI portable computer and an octopter UAV. The system was assessed in aerial mode using an UAV octopter developed by SensorMap Company. The resulting point density in a plot with trees concentration was also evaluated. The point density of this device is lower than conventional Airborne Laser Systems but the results showed that altimetric accuracy with this system is around 30 cm, which is acceptable for forest applications. The main advantages of this system are their low weight and low cost, which make it attractive for several applications.

scholarly journals Fusing Stereo Camera and Low-Cost Inertial Measurement Unit for Autonomous Navigation in a Tightly-Coupled Approach

2014 ◽  
Vol 68 (3) ◽  
pp. 434-452 ◽  
Author(s):  
Zhiwen Xian ◽  
Xiaoping Hu ◽  
Junxiang Lian
Keyword(s):  
Autonomous Navigation ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Three Dimensional ◽  
Fast Response ◽  
Location Estimation ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Stereo Camera

Exact motion estimation is a major task in autonomous navigation. The integration of Inertial Navigation Systems (INS) and the Global Positioning System (GPS) can provide accurate location estimation, but cannot be used in a GPS denied environment. In this paper, we present a tight approach to integrate a stereo camera and low-cost inertial sensor. This approach takes advantage of the inertial sensor's fast response and visual sensor's slow drift. In contrast to previous approaches, features both near and far from the camera are simultaneously taken into consideration in the visual-inertial approach. The near features are parameterised in three dimensional (3D) Cartesian points which provide range and heading information, whereas the far features are initialised in Inverse Depth (ID) points which provide bearing information. In addition, the inertial sensor biases and a stationary alignment are taken into account. The algorithm employs an Iterative Extended Kalman Filter (IEKF) to estimate the motion of the system, the biases of the inertial sensors and the tracked features over time. An outdoor experiment is presented to validate the proposed algorithm and its accuracy.

scholarly journals Constrained ESKF for UAV Positioning in Indoor Corridor Environment Based on IMU and WiFi

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 391
Author(s):  
Zhonghan Li ◽  
Yongbo Zhang
Keyword(s):  
Data Fusion ◽  
Autonomous Navigation ◽  
Low Cost ◽  
Optimization Method ◽  
Satellite System ◽  
Fusion Algorithm ◽  
K Nearest Neighbors ◽  
Positioning Accuracy ◽  
Spatial Features ◽  
Global Navigation Satellite

The indoor autonomous navigation of unmanned aerial vehicles (UAVs) is the current research hotspot. Unlike the outdoor broad environment, the indoor environment is unknown and complicated. Global Navigation Satellite System (GNSS) signals are easily blocked and reflected because of complex indoor spatial features, which make it impossible to achieve positioning and navigation indoors relying on GNSS. This article proposes a set of indoor corridor environment positioning methods based on the integration of WiFi and IMU. The zone partition-based Weighted K Nearest Neighbors (WKNN) algorithm is used to achieve higher WiFi-based positioning accuracy. On the basis of the Error-State Kalman Filter (ESKF) algorithm, WiFi-based and IMU-based methods are fused together and realize higher positioning accuracy. The probability-based optimization method is used for further accuracy improvement. After data fusion, the positioning accuracy increased by 51.09% compared to the IMU-based algorithm and by 66.16% compared to the WiFi-based algorithm. After optimization, the positioning accuracy increased by 20.9% compared to the ESKF-based data fusion algorithm. All of the above results prove that methods based on WiFi and IMU (low-cost sensors) are very capable of obtaining high indoor positioning accuracy.

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