Conceptual design and error analysis of a cable-driven parallel robot

This paper develops the conceptual design and error analysis of a cable-driven parallel robot (CDPR). The earlier error analysis of CDPRs generally regarded the cable around the pulley as a center point and neglected the radius of the pulleys. In this paper, the conceptual design of a CDPR with pulleys on its base platform is performed, and an error mapping model considering the influence of radius of the pulleys for the CDPR is established through kinematics analysis and a full matrix complete differential method. Monte Carlo simulation is adopted to deal with the sensitivity analysis, which can directly describe the contribution of each error component to the total orientation error of the CDPR by virtue of the error modeling. The results show that the sensitivity coefficients of pulleys’ geometric errors and geometric errors of the cables are relatively larger, which confirms that the cable length errors and pulleys’ geometric errors should be given higher priority in design and processing.

Learning Rotated Inscribed Ellipse for Oriented Object Detection in Remote Sensing Images

Oriented object detection in remote sensing images (RSIs) is a significant yet challenging Earth Vision task, as the objects in RSIs usually emerge with complicated backgrounds, arbitrary orientations, multi-scale distributions, and dramatic aspect ratio variations. Existing oriented object detectors are mostly inherited from the anchor-based paradigm. However, the prominent performance of high-precision and real-time detection with anchor-based detectors is overshadowed by the design limitations of tediously rotated anchors. By using the simplicity and efficiency of keypoint-based detection, in this work, we extend a keypoint-based detector to the task of oriented object detection in RSIs. Specifically, we first simplify the oriented bounding box (OBB) as a center-based rotated inscribed ellipse (RIE), and then employ six parameters to represent the RIE inside each OBB: the center point position of the RIE, the offsets of the long half axis, the length of the short half axis, and an orientation label. In addition, to resolve the influence of complex backgrounds and large-scale variations, a high-resolution gated aggregation network (HRGANet) is designed to identify the targets of interest from complex backgrounds and fuse multi-scale features by using a gated aggregation model (GAM). Furthermore, by analyzing the influence of eccentricity on orientation error, eccentricity-wise orientation loss (ewoLoss) is proposed to assign the penalties on the orientation loss based on the eccentricity of the RIE, which effectively improves the accuracy of the detection of oriented objects with a large aspect ratio. Extensive experimental results on the DOTA and HRSC2016 datasets demonstrate the effectiveness of the proposed method.

Modelling collective navigation via non-local communication

Collective migration occurs throughout the animal kingdom, and demands both the interpretation of navigational cues and the perception of other individuals within the group. Navigational cues orient individuals towards a destination, while it has been demonstrated that communication between individuals enhances navigation through a reduction in orientation error. We develop a mathematical model of collective navigation that synthesizes navigational cues and perception of other individuals. Crucially, this approach incorporates uncertainty inherent to cue interpretation and perception in the decision making process, which can arise due to noisy environments. We demonstrate that collective navigation is more efficient than individual navigation, provided a threshold number of other individuals are perceptible. This benefit is even more pronounced in low navigation information environments. In navigation ‘blindspots’, where no information is available, navigation is enhanced through a relay that connects individuals in information-poor regions to individuals in information-rich regions. As an expository case study, we apply our framework to minke whale migration in the northeast Atlantic Ocean, and quantify the decrease in navigation ability due to anthropogenic noise pollution.

Pose Estimation of Excavator Manipulator Based on Monocular Vision Marker System

Excavation is one of the broadest activities in the construction industry, often affected by safety and productivity. To address these problems, it is necessary for construction sites to automatically monitor the poses of excavator manipulators in real time. Based on computer vision (CV) technology, an approach, through a monocular camera and marker, was proposed to estimate the pose parameters (including orientation and position) of the excavator manipulator. To simulate the pose estimation process, a measurement system was established with a common camera and marker. Through comprehensive experiments and error analysis, this approach showed that the maximum detectable depth of the system is greater than 11 m, the orientation error is less than 8.5°, and the position error is less than 22 mm. A prototype of the system that proved the feasibility of the proposed method was tested. Furthermore, this study provides an alternative CV technology for monitoring construction machines.

AR-Based Navigation Using RGB-D Camera and Hybrid Map

Current pedestrian navigation applications have been developed for the smartphone platform and guide users on a 2D top view map. The Augmented Reality (AR)-based navigation from the first-person view could provide a new experience for pedestrians compared to the current navigation. This research proposes a marker free system for AR-based indoor navigation. The proposed system adopts the RGB-D camera to observe the surrounding environment and builds a point cloud map using Simultaneous Localization and Mapping (SLAM) technology. After that, a hybrid map is developed by integrating the point cloud map and a floor map. Finally, positioning and navigation are performed on the proposed hybrid map. In order to visualize the augmented navigation information on the real scene seamlessly, this research proposes an orientation error correction method to improve the correctness of navigation. The experimental results indicated that the proposed system could provide first-person view navigation with satisfactory performance. In addition, compared to the baseline without any error correction, the navigation system with the orientation error correction method achieved significantly better performance. The proposed system is developed for the smart glasses and can be used as a touring tool.

Modelling collective navigation via nonlocal communication

Collective migration occurs throughout the animal kingdom, and demands both the interpretation of navigational cues and the perception of other individuals within the group. Navigational cues orient individuals toward a destination, while it is hypothesised that communication between individuals enhances navigation through a reduction in orientation error. We develop a mathematical model of collective navigation that synthesises navigational cues and perception of other individuals. Crucially, this approach incorporates the uncertainty inherent to cue interpretation and perception in the decision making process, which can arise due to noisy environments. We demonstrate that collective navigation is more efficient than individual navigation, provided a threshold number of other individuals are perceptible. This benefit is even more pronounced in low navigation information environments. In navigation ``blindspots'', where no information is available, navigation is enhanced through a relay that connects individuals in information-poor regions to individuals in information-rich regions. As an expository case study, we apply our framework to minke whale migration in the North East Atlantic Ocean, and quantify the decrease in navigation ability due to anthropogenic noise pollution.

Short Review of True-North Alignment Method on the Field Demonstrating the benefits of the use of an Optical Gyrocompass

<p><span><span>To install a seismometer with a properly defined orientation - inside a vault or into a borehole - as a single station including various instruments or as a part of an array - an ‘adequate’ tool and an ‘absolute’ reference are needed.</span></span></p><p><span><span>In the past, and sometimes it persists nowadays, magnetic North have been used as a reference for Z-orientation of seismic station. Several studies have extensively measured the orientation error that have been made with this method, using an optical gyrocompass providing True-North as a reference, and their work will be summarized here.</span></span></p><p><span><span>In these studies, optical Gyrocompass is said to be the good solution, even if it is too heavy, expensive, and difficult to export. This paper will explain how iXblue has overcome these limitations to design the new-born Seistans Optical Gyrocompass.</span></span></p><p><span><span>Moreover, to aim True-North with a reliable accuracy is not the only think you need to do on the field. The method to transfer the North-line from the gyrocompass to the instrument to aligned must not induce errors that ruined the accuracy obtained using state-of-the-art gyrocompass. So an exhaustive study of the different ways to transfer the orientation from the compass to the aligned sensor will be presented, and corresponding added uncertainty will be evaluated, which is a good way to promote good practice on the field.</span></span></p><p><span><span>Finally, some figures will be gathered and shared from literature to quantify the precision needed for the alignment of a seismic sensor. There are today so few papers about this important matter that it is worth to spread their information.</span></span></p>