Position Mapping Research Articles

Mapping tropical forest trees across large areas with lightweight cost-effective terrestrial laser scanning

Key messageWe used lightweight terrestrial laser scanning (TLS) to detect over 3000 stems per hectare across a 12-ha permanent forest plot in French Guiana, 81% of them < 10 cm in trunk diameter. This method retrieved 85% of the trees of a classic inventory. Finally, TLS revealed that stem positions of the classic inventory had geolocation errors of up to 6 m.ContextAccurate position mapping of tropical rainforest trees is crucial for baseline studies of tropical forest ecology but is labor-intensive. Terrestrial lidar scanning (TLS) is broadly used in temperate forest inventories, but its use in rainforests is restricted to the determination of individual tree volumes within small survey areas.AimsMapping tree stems across one large (12-ha) rainforest plot, including trees less than 10 cm DBH, and evaluating the precision of traditional mapping approaches.MethodsWe used lightweight TLS, co-registered the acquisitions, and developed a new efficient algorithm to process the TLS data.ResultsWe detected 36,422 stems of which 29,665 (81%) were < 10 cm in diameter at breast height (DBH). Of the trees ≥ 10 cm DBH previously censused in the plot, 85% were identified by TLS. Automatic DBH estimation from TLS data had an RMSE of 6 cm. RMSE was improved to 3 cm by a manual verification of the shape and quality of the stem points. The initial census map had substantial bias in tree geolocation with a maximum value around 6 m.ConclusionLightweight TLS technology is a promising tool for the estimation of stem tapering and volume. Here, we show that it also facilitates the establishment of large tropical forest inventories, by improving the positioning of trees, thus increasing the accuracy of forest inventories and their cost-effectiveness.

A novel method for calibration and verification of roadside millimetre‐wave radar

Roadside perception systems commonly rely on millimetre-wave radars that are stationary. Obtaining global coordinates of radar detection targets requires calibration of radars installed on roadways, which is dangerous if performed via conventional methods. Hazards such as live traffic, particularly on expressways, make safe calibration difficult without road closures. To avoid these issues, this paper proposes a novel calibration method for roadside millimetre-wave radar by using high-definition maps to provide global positioning for radar detection targets, combined with vehicle trajectory data from live traffic. After clustering collected traffic data, a polynomial curve fit provides the shape of lane centrelines. Calibration parameters for the relative-to-global position mapping are then obtained by matching fitted curve sample points to points in high-definition maps using non-linear optimization. The calibration results are verified experimentally using a connected vehicle and roadside unit on an urban street, demonstrating that the proposed method meets lane-level precision requirements for V2X applications. This data-driven method borrows live traffic for calibration and hence is safer and more convenient compared to existing calibration methods.

Cooperative Three-Dimensional Position Mapping Based on Received Signal Strength Measurements: Algorithm Design and Field Test

This paper presents a new approach to accurately and efficiently identifying a large number of wireless devices blindly installed to known three-dimensional installation/fitting points, based on received signal strengths (RSSs) between the devices. The approach is non-trivial because of the factorial, mapping nature of the considered problem, the multiplicative ranging errors of the RSS measurements (with standard deviation of 5–7 dB), and the requirement of high mapping accuracy in many internet-of-things (IoT) applications, e.g., industrial IoT and aircraft. The consideration of a structured environment where the set of candidate node positions is known beforehand shifts the problem of interest from a pure position estimation problem to a position assignment problem. The key idea of the proposed approach is that we interpret the position mapping problem with a probabilistic graphical model, where the factorial nature of mapping (more specifically, the mutual exclusiveness of devices at every installation point) is fully captured. A max-product belief propagation is designed against the probabilistic graph, to estimate the max-marginal position distribution of each device. The Kuhn-Munkres algorithm is applied to preserve the mutual exclusiveness of devices throughout the belief propagation and to decide device locations based on the estimated position distributions. Large-scale simulations and field tests are carried out, showing that the new approach achieves close-to-100% accuracy in simulations with hundreds of blindfolded devices under RSS measurement errors with standard deviation of 5–7 dB. Our approach also achieves 100% accuracy in all field trials with 76 devices inside the cabin of a Fokker 100 airplane, dramatically outperforming baseline techniques.

Development and evaluation of a seed position mapping system

With the development of precision agriculture, individual plant care systems have become an important research topic. These systems require accurate and reliable information about the position of individual plants. Seed position mapping, an important method of accurate plant positioning techniques, can obtain seed location data directly in planting stage. The utilization of seed location data is maximized by providing references for the field managements such as intra-row weeding, fertilizer and pesticide application. This study presented the design of a seed mapping system for corn planters in high-position seeding method (HSM). An experimental study of the designed mapping system was performed to evaluate its performance with a four-row planter. The seed firmer (SF) which can reduce seed bouncing and the limiting plate (LP) which can disable the parallel four-bar linkage (PFL) are used to modify the four-row planter. Each planter unit had been modified differently (with SF and LP added, without SF and LP added, with only LP added, with only SF added). The accuracy of the seed position mapping system was evaluated for different operation speed (3, 5, and 7 km/h), seed spacing (20, 30, and 40 cm), and the global positing system (GPS) frequency (1, 5, and 10 Hz) by the distance deviation (DD) and the location quality index (LQI), where DD is the distance deviation between the predicted and actual seed locations, while LQI is defined as the percentage of seeds with a DD < 5 cm. Field tests show that the application of SF can decrease DD and increase LQI immensely: the average decrease of DD is 19.85 mm in the row with SF compared with that without SF, while the average increase of LQI is 29.4%. The application of LP has no significant impact on DD and LQI under experimental conditions. The DD was highly significant influenced by operation speed and seed spacing (p < 0.01), but significant influenced by GPS frequency (p < 0.05). The LQI was highly significant influenced by operation speed (p < 0.01), significant influenced by seed spacing (p < 0.05), but not significant influenced by GPS frequency (p > 0.05). Slower operation speed and larger seed spacing help to improve the mapping accuracy, achieving lower DD and higher LQI. The maximum operating speed of proposed mapping system is 3 km/h, the average DD and LQI in the presence of SF under this condition were 24.4 mm and 91.3%. The mapping accuracy under such conditions is satisfactory.

The Advantages Position Mapping of “Bee Jay Bakau Resort” Ecotourism

Bee Jay Bakau Resort (BJBR) is one of the main tourist destinations in Probolinggo City that utilizes the mangrove ecosystem. The study aims to analyze the advantages position mapping of BJBR. The study uses correlational approach with accidental sampling of 70 respondents. Data were analyzed by using exploratory factor analysis (EFA) and correspondence analysis (CA) with 16 attributes. This study assessed three mangrove ecotourism sites in East Java. The main factors that influence tourists visiting BJBR are tourist attractions, prices, tourism completeness and safety, mangrove preservation, as well as service friendliness. BJBR has tourism advantages in the form of complete facilities and completeness of its attractions. Meanwhile, the advantages of Wonorejo Surabaya mangrove ecotourism are among others: the availability of education related to mangroves and the cleanliness of the facilities. On the other side, The Clungup Mangrove Conservation Malang has the advantages in the form of mangrove conservation, tourism beauty, tourism memories, and tourism safety. BJBR managers need to improve the sustainability of the mangrove forest ecosystem and educational facilities regarding the benefits of mangroves in order to have a positive impact on tourists.

Automatic roller path tracking and mapping for pavement compaction using infrared thermography

AbstractCompaction is an important task in asphalt pavement construction. It ensures high quality of the pavement to provide required long‐term performance. Intelligent compaction (IC) integrated with global positioning system (GPS) is an innovative technology to help control the compaction quality of asphalt pavement by continuously providing the operator with the roller's current position and the number of rolling passes. However, the high equipment cost and signal disturbance are two identified issues when adopting the GPS for position estimation. This paper proposed a thermal‐based method for real‐time roller path tracking and mapping in pavement compaction operations. In this method, first, the incremental roller motion between each two consecutive frames was jointly estimated via calculation of the roller's heading direction by exploiting the pavement boundary information and the roller's translation using the optical flow technique. Then, the accuracy of the estimated incremental motion was optimized by incorporation of the roller's lateral position estimated by a position optimization model proposed by the authors. Finally, the roller's global location was estimated by chaining frame‐by‐frame roller motions recursively. Both laboratory and field validations were conducted to examine the performance of the proposed method, leading to the maximum mean absolute errors along the lateral direction to be 5.2 mm and 3.3 cm, respectively, and the maximum cumulative error rates along the longitudinal direction to be 0.85% and 0.73%, respectively. The validation results signified the method's potential as a low‐cost and applicable alternative to the GPS in the current IC technology for roller's position tracking and mapping.

Application of Virtual Reality Technology (VR) in Practice Teaching of Sports Rehabilitation Major

Patients who can receive rehabilitation training provide two types of feedback. This is the biggest advantage of virtual reality technology for rehabilitation training, and at the same time can improve the patient’s perception of rehabilitation results. This article aims to study the application of virtual reality technology (vr) in sports rehabilitation professional practice teaching. This paper uses the research method of virtual scene position mapping. The virtual scene position mapping is based on the virtual realization technology of upper limb rehabilitation training, which is manipulated by the movement of the patient’s upper limbs. In the experiment, all the students in the first and second classes of a sports rehabilitation major in a local university were subjected to theoretical tests and practical ability assessments to all the students in the first and second classes of the sports rehabilitation major. Experimental data shows that the excellent rate and passing rate of the experimental class’s practical ability test are much higher than those of the control class. Therefore, it can be concluded that the application of virtual reality technology to sports rehabilitation teaching is beneficial to the improvement of learners’ practical ability. The experimental results show that the test excellence rate of the experimental class is 24.2% higher than that of the control class, and the passing rate is 12% higher. Therefore, applying virtual reality technology to sports rehabilitation education can stimulate people’s interest in learning. The virtual environment is very similar to the real world, and the motor skills learned in the virtual environment can be successfully transferred to the real world.

Mapping as a strategic tool for evidencing social values and supporting joined-up decision making in Reading, England

ABSTRACT Social value is high on policy agendas in the UK but there is little agreement on the definition of social value in the context of the built environment or on how the gathering of social value data might be spatialized. This paper gives an account of a project at the University of Reading, the aim of which was to develop a pragmatic methodology for collecting social value data with local communities. In response to rich information collected through workshops, a practice-based approach was taken, whereby 14 handmade community maps were drawn digitally, following a consistent set of drawing rules. The resultant multi-layered vector maps gathered and collated different interpretations of value and converted them into an accessible visual format. This supported dissemination, feedback and visual analysis with both participants and the Local Authority. In turn, the research sought to position mapping as a strategic tool for revealing common values and communicating potential in the built environment, with the aim of developing value-based knowledge particularly useful to early design, and decision-making, processes around strategic land management.

Full-Dimensional Intuitive Motion Mapping Strategy for Minimally Invasive Surgical Robot With Redundant Passive Joints

AbstractAdding redundant passive joints to a robotic arm is an effective way to make the robot overcome the inherent incision constraint of minimally invasive surgery (MIS). However, due to the limited motion accuracy, it is difficult to realize full-dimensional intuitive motion based on traditional multi-axis coordinated control technology in this kind of MIS robots. To solve this problem, a separated position and orientation mapping strategy for MIS robot with redundant passive joints is proposed in the paper. The position and orientation mapping of the strategy are realized by coordinate motion control and joint direct control technique, respectively. To realize the intuitive motion under this condition, an inverse motion mapping method is further proposed. Compared with the existing mapping strategy, the proposed strategy is much more compact as the orientation mapping is greatly simplified. A large number of in vivo trials based on the newly developed prototype have been conducted and results fully verify the effectiveness of the proposed strategy.

Ghost Imaging with Deep Learning for Position Mapping of Weakly Scattered Light Source

We propose ghost imaging (GI) with deep learning to improve detection speed. GI, which uses an illumination light with random patterns and a single-pixel detector, is correlation-based and thus suitable for detecting weak light. However, its detection time is too long for practical inspection. To overcome this problem, we applied a convolutional neural network that was constructed based on a classification of the causes of ghost image degradation. A feasibility experiment showed that when using a digital mirror device projector and a photodiode, the proposed method improved the quality of ghost images.

A Delta‐Parallel‐Inspired Human Machine Interface by Using Self‐Powered Triboelectric Nanogenerator Toward 3D and VR/AR Manipulations

AbstractIn recent years, human‐machine interface technology has entered a period of rapid development in the global scope. It has gradually expanded from the initial field of medical rehabilitation to engineering bionics, virtual reality, space technology, deep‐sea assignments, atomic energy technology, remote education, and other areas. Herein, an innovative, self‐powered delta‐parallel human‐machine interface (DT‐HMI) for 3D sensing and control is proposed. By using three pairs of triboelectric nanogenerator (TENG) sensing gears based on both contact‐separation and sliding modes of triboelectric effect, the positive and negative rotation of the gears and rotation angles can be obtained. According to the forward‐and‐inverse kinematics of parallel robots, the spatial position and motion attitude of the platform can be calculated. The three pairs of TENG sensing gears with six electrodes define the 512 virtual sensing pixels. The low‐cost, simple‐designed DT‐HMI controller can achieve remote control and even spatial position mapping. Accordingly, the combination of output signals enables the realization of a highly scalable and self‐powered triboelectric interface toward a variety of application scenarios, including 2/3D control, VR/AR, interaction, robotics, etc.

Characterization of the Adaptation to Visuomotor Rotations in the Muscle Synergies Space.

The adaptation to visuomotor rotations is one of the most studied paradigms of motor learning. Previous literature has presented evidence of a dependency between the process of adaptation to visuomotor rotations and the constrains dictated by the workspace of the biological actuators, the muscles, and their co-activation strategies, modeled using muscle synergies analysis. To better understand this relationship, we asked a sample of healthy individuals (N = 7) to perform two experiments aiming at characterizing the adaptation to visuomotor rotations in terms of rotations of the activation space of the muscle synergies during isometric reaching tasks. In both experiments, subjects were asked to adapt to visual rotations altering the position mapping between the force exerted on a fixed manipulandum and the movement of a cursor on a screen. In the first experiment subjects adapted to three different visuomotor rotation angles (30°, 40°, and 50° clockwise) applied to the whole experimental workspace. In the second experiment subjects adapted to a single visuomotor rotation angle (45° clockwise) applied to eight different sub-spaces of the whole workspace, while also performing movements in the rest of the unperturbed workspace. The results from the first experiment confirmed the hypothesis that visuomotor rotations induce rotations in the synergies activation workspace that are proportional to the visuomotor rotation angle. The results from the second experiment showed that rotations affecting limited sub-spaces of the whole workspace are adapted for by rotating only the synergies involved in the movement, with an angle proportional to the distance between the preferred angle of the synergy and the sub-space covered by the rotation. Moreover, we show that the activation of a synergy is only rotated when the sub-space covered by the visual perturbation is applied at the boundaries of the workspace of the synergy. We found these results to be consistent across subjects, synergies and sub-spaces. Moreover, we found a correlation between synergies and muscle rotations further confirming that the adaptation process can be well described, at the neuromuscular level, using the muscle synergies model. These results provide information on how visuomotor rotations can be used to induce a desired neuromuscular response.

Assist-as-needed policy for movement therapy using telerobotics-mediated therapist supervision

In this paper, a new impedance-based teleoperation strategy is proposed for assist-as-needed tele-rehabilitation via a multi-DOF telerobotic system having patient–master and therapist–slave interactions. Unlike a regular teleoperation system and as the main contribution of this work to minimize the therapist’s movements, the therapist’s hand only follows the patient’s deviation from the target trajectory. Also it provides a better perception of the patient’s problems in motor control to the therapist The admissible deviation of the patient’s limb from a reference target trajectory is governed by an impedance model responding to both patient’s and therapist’s interaction forces. As the other benefit of this framework, two sources of assistance to the patient are delivered through the master robot: (1) the adjustable impedance model, and (2) the force applied by the therapist to the slave robot. The assistive impedance model is beneficial to reduce magnitudes of the required force from the therapist and decrease his/her intervention. This results in delaying and declining the therapist’s muscle fatigue in time-consuming movement therapies. Bilateral nonlinear control laws with two types of adaptation laws are designed for the nonlinear teleoperation system. The Lyapunov stability proof of the teleoperation system and the stability of the impedance model enhance the patient’s and therapist’s safety even in the presence of modeling uncertainties of the multi-DOF telerobotic system. The performance of the proposed bilateral impedance-based strategy is experimentally investigated using different impedance parameters adjusted based on the patient’s characteristics (e.g., involuntary tremor) and disabilities (e.g., insufficient actuation force). The experiments are performed by a healthy person (as the therapist), a mechanical test bed and a volunteer (simulating the patients’ characteristics). A new force–position mapping from Cartesian to Normal–Tangential (N–T) coordinates is utilized between the master and slave workspaces and compared with typical Cartesian to Cartesian projection.

A Blockchain-Based Traceable IP Copyright Protection Algorithm

Current Intellectual Property (IP) copyright protection technologies have low efficiency of authority management, traceability, and scalability. In this work, a blockchain-based IP copyright protection algorithm is proposed to address these issues by establishing a mathematical model of quadratic matrix transformation for IP circuit trading. This algorithm proposes the design of a distributed random embedding mechanism and position mapping function that, when IP trading occurs in blockchain, the traceable mapping function can trace the copyright information in IP trading with the mapping factor. Besides, this work analyzes the credibility, transparency, overhead, and complexity. Experimental results show that the proposed algorithm can resist replaying attacks, yet the copyright information can be rapidly retrieved after suffered from attacks. Still, the proposed algorithm has higher security, stability, and traceability.

Characterization and layer thickness mapping of two-dimensional MoS2 flakes via hyperspectral line-scanning microscopy

A micro-reflectance imaging system based on hyperspectral line-scanning microscope is developed for surface characterization and thickness mapping of two-dimensional MoS2. The hyperspectral datacube of region of interest (120 × 200 μm2) is obtained with microscale spatial resolution. Single-band quantitative analysis shows distributions of different thicknesses with wavelength variations. The excitonic peak with position around 655 nm is measured by differential reflectance analysis. Peak position mapping is employed for imaging MoS2 flakes with specific thickness and reconstructed images perform the same region of interest with high accuracy. The developed micro-reflectance imaging system has applications in laboratory analyses and industrial monitoring of 2D materials.

Position and momentum mapping of vibrations in graphene nanostructures.

Propagating atomic vibrational waves-phonons-determine important thermal, mechanical, optoelectronic and transport characteristics of materials. Thus a knowledge of phonon dispersion (that is, the dependence of vibrational energy on momentum) is a key part of our understanding and optimization of a material's behaviour. However, the phonon dispersion of a free-standing monolayer of a two-dimensional material such as graphene, and its local variations, have remained elusive for the past decade because of the experimental limitations of vibrational spectroscopy. Even though electron energyloss spectroscopy (EELS) in transmission has recently been shown to probe local vibrational charge responses1-4, such studies are still limited by momentum space integration due to the focused beam geometry; they are also restricted to polar materials such as boron nitride or oxides1-4, in which huge signals induced by strong dipole moments are present. On the other hand, measurements on graphene performed by inelastic X-ray (neutron) scattering spectroscopy5-7 or EELS in reflection8,9 do not have any spatial resolution and require large microcrystals. Here we provide a new pathway to determine phonon dispersions down to the scale of an individual free-standing graphene monolayer by mapping the distinct vibrational modes for a large momentum transfer. The measured scattering intensities are accurately reproduced and interpreted with density functional perturbation theory10. Additionally, a nanometre-scale mapping of selected momentum-resolved vibrational modes using graphene nanoribbon structures has enabled us to spatially disentangle bulk, edge and surface vibrations. Our results are a proof-of-principle demonstration of the feasibility of studying local vibrational modes in two-dimensional monolayer materials at the nanometre scale.

다중 자기센서를 이용한 실내 자기 지도 기반 보행자 위치 검출 정확도 향상 알고리즘

This research proposes a indoor magnetic map matching algorithm that improves the position accuracy by employing multiple magnetic sensors and probabilistic candidate weighting function. Since the magnetic field is easily distorted by the surrounding environment, the distorted magnetic field can be used for position mapping, and multiple sensor configuration is useful to improve mapping accuracy. Nevertheless, the position error is likely to increase because the external magnetic disturbances have repeated pattern in indoor environment and several points have similar magnetic field distortion characteristics. Those errors cause large position error, which reduces the accuracy of the position detection. In order to solve this problem, we propose a method to reduce the error using multiple sensors and likelihood boundaries that uses human walking characteristics. Also, to reduce the maximum position error, we propose an algorithm that weights according to their importance. We performed indoor walking tests to evaluate the performance of the algorithm and analyzed the position detection error rate and maximum distance error. From the results we can confirm that the accuracy of position detection is greatly improved.

Enhancing Machine Reading Comprehension With Position Information

When people do the reading comprehension, they often try to find the words from the passages which are similar to the question words first. Then people deduce the answer based on the context around these similar words. Therefore, the position information may be helpful in finding the answer rapidly and is useful for reading comprehension. However, previous attention-based machine reading comprehension models typically focus on the interaction between the question and the context representation without considering the position information. In this paper, we introduce the position information to machine reading comprehension and investigate the performance of the position information. The position information is experimented in three different ways: 1) position encoder; 2) attention mechanism; and 3) position mapping embedding. By experimenting on TriviaQA dataset, we have demonstrated the effectiveness of position information.

Varying Speed Rate Controller for Human–Robot Teleoperation Based on Muscle Electrical Signals

With the emergence of industrial robots in recent decades, advancing the technology that drives human-robot interaction has become a research hotspot. However, the control of human-robot interaction using human gestures has presented some challenges when applied to the industrial environment. For example, when a robot is controlled with a hand motion, the hand movement space may be smaller than the robot's working space, making it difficult to meet the robot's space and accuracy requirements. The research herein was centered on building interactive scenarios through unit software, and gesture recognition sensors were used to collect spatial information about the hand. A position mapping algorithm was used to map the position of the hand to the robot end-effector and a virtual robot space constraint was added to collectively allow users to control the robot's movements. In the experiment, volunteers were asked to control the robot by using constant speed ratio (Ratio of robot speed to input value) or changing speed ratio. The speed ratio affected the stability of the experiment, adding electromyography can improve the stability. The first innovation was the use of human muscle information as input information, adding it to the interaction based on unity. The second innovation was using an algorithm to change the mapping speed ratio according to the electromyography information provided. This was the first time that electromyography was used to change the mapping speed ratio of human-robot interactions, which may enable further advancements in human-robot interaction.

Kinematic and Kinetostatic Analysis of Parallel Manipulators with Emphasis on Position, Motion, and Actuation Singularities

SummaryThis paper provides a contribution to the singularity analysis of the parallel manipulators by introducing the position singularities in addition to the motion and actuation singularities. The motion singularities are associated with the linear velocity mapping between the task and joint spaces. So, they are the singularities of the relevant Jacobian matrices. On the other hand, the position singularities are associated with the nonlinear position mapping between the task and joint spaces. So, they are encountered in the position-level solutions of the forward and inverse kinematics problems. In other words, they come out irrespective of the velocity mapping and the Jacobian matrices. Considering these distinctions, a kinematic singularity is denoted here by one of the four acronyms, which are PSFK (position singularity of forward kinematics), PSIK (position singularity of inverse kinematics), MSFK (motion singularity of forward kinematics), and MSIK (motion singularity of inverse kinematics). There may also occur an actuation singularity (ACTS) concerning the kinetostatic relationships that involve forces and moments. However, it is verified that an ACTS is the same as an MSFK. Each singularity induces different consequences in the joint and task spaces. A PSFK imposes a constraint on the active joint variables and makes the end-effector position indefinite and uncontrollable. Therefore, it must be avoided. An MSFK imposes a constraint on the rates of the active joint variables and makes the end-effector motion indefinite and easily perturbable. Besides, since it is also an ACTS, it causes the actuator torques or forces to grow without bound. Therefore, it must also be avoided. On the other hand, a PSIK imposes a constraint on the end-effector position but provides freedom for the active joint variables. Similarly, an MSIK imposes a constraint on the end-effector motion but provides freedom for the rates of the active joint variables. A PSIK or MSIK need not be avoided if the constraint it imposes on the position or motion of the end-effector is acceptable or if the task can be planned to be compatible with that constraint. Besides, with such a compatible task, a PSIK or MSIK may even be advantageous, because the freedom it provides for the active joint variables can sometimes be used for a secondary purpose. This paper is also concerned with the multiplicities of forward kinematics in the assembly modes of the manipulator and the multiplicities of inverse kinematics in the posture modes of the legs. It is shown that the assembly mode changing poses of the manipulator are the same as the MSFK poses, and the posture mode changing poses of the legs are the same as the MSIK poses.