Instant Basketball Defensive Trajectory Generation

Tactic learning in virtual reality (VR) has been proven to be effective for basketball training. Endowed with the ability of generating virtual defenders in real time according to the movement of virtual offenders controlled by the user, a VR basketball training system can bring more immersive and realistic experiences for the trainee. In this article, an autoregressive generative model for instantly producing basketball defensive trajectory is introduced. We further focus on the issue of preserving the diversity of the generated trajectories. A differentiable sampling mechanism is adopted to learn the continuous Gaussian distribution of player position. Moreover, several heuristic loss functions based on the domain knowledge of basketball are designed to make the generated trajectories assemble real situations in basketball games. We compare the proposed method with the state-of-the-art works in terms of both objective and subjective manners. The objective manner compares the average position, velocity, and acceleration of the generated defensive trajectories with the real ones to evaluate the fidelity of the results. In addition, more high-level aspects such as the empty space for offender and the defensive pressure of the generated trajectory are also considered in the objective evaluation. As for the subjective manner, visual comparison questionnaires on the proposed and other methods are thoroughly conducted. The experimental results show that the proposed method can achieve better performance than previous basketball defensive trajectory generation works in terms of different evaluation metrics.

Hyper-Redundant Manipulator Capable of Adjusting Its Non-Uniform Curvature with Discrete Stiffness Distribution

Hyper-redundant manipulators are widely used in minimally invasive surgery because they can navigate through narrow passages in passive compliance with the human body. Although their stability and dexterity have been significantly improved over the years, we need manipulators that can bend with appropriate curvatures and adapt to complex environments. This paper proposes a design principle for a manipulator capable of adjusting its non-uniform curvature and predicting the bending shape. Rigid segments were serially stacked, and elastic fixtures in the form of flat springs were arranged between hinged-slide joint segments. A manipulator with a diameter of 4.5 mm and a length of 28 mm had been fabricated. A model was established to predict the bending shape through minimum potential energy theory, kinematics, and measured stiffnesses of the flat springs. A comparison of the simulation and experimental results indicated an average position error of 3.82% of the endpoints when compared to the total length. With this modification, the manipulator is expected to be widely used in various fields such as small endoscope systems and single-port robot systems.

An Indoor Localization Method Based on the Combination of Indoor Map Information and Inertial Navigation with Cascade Filter

The specific objective of this study is to propose a low-cost indoor navigation framework with nonbasic equipment by combining inertial sensors and indoor map messages. The proposed pedestrian navigation framework consists of a lower filter and an upper filter. In the lower filter which is designed based on the Kalman filter, the adaptive zero velocity detection algorithm is used to detect the zero velocity interval at different motion speeds, and then, zero velocity update is applied to rectify the inertial navigation solutions’ errors. In the upper filter which is designed based on the nonrecursive Bayesian filter, the map matching method with nonrecursive Bayesian filter is adopted to fuse the map prior information and the lower filter estimation results to correct the errors of navigation. The position estimation presented in this study achieves an average position error of 0.53 m compared to the ZUPT-aided inertial navigation system (INS) method under different motion states. The proposed pedestrian navigation algorithm achieves an average position error of 0.54 m as compared to the ZUPT-aided INS method among the different tested distances. The proposed framework simplifies the indoor positioning system under multiple motion speed conditions by ensuring the accuracy and stability property. The effectiveness and accuracy of the proposed framework are experimentally verified in various real-world scenarios.

Satellite Availability and Service Performance Evaluation for Next-Generation GNSS, RNSS and LEO Augmentation Constellation

Positioning accuracy is affected by the combined effect of user range errors and the geometric distribution of satellites. Dilution of precision (DOP) is defined as the geometric strength of visible satellites. DOP is calculated based on the satellite broadcast or precise ephemerides. However, because the modernization program of next-generation navigation satellite systems is still under construction, there is a lack of real ephemerides to assess the performance of next-generation constellations. Without requiring real ephemerides, we describe a method to estimate satellite visibility and DOP. The improvement of four next-generation Global Navigation Satellite Systems (four-GNSS-NG), compared to the navigation constellations that are currently in operation (four-GNSS), is statistically analyzed. The augmentation of the full constellation the Quasi-Zenith Satellite System (7-QZSS) and the Navigation with Indian Constellation (11-NavIC) for regional users and the low Earth orbit (LEO) constellation enhancing four-GNSS performance are also analyzed based on this method. The results indicate that the average number visible satellites of the four-GNSS-NG will reach 44.86, and the average geometry DOP (GDOP) will be 1.19, which is an improvement of 17.3% and 7.8%, respectively. With the augmentation of the 120-satellite mixed-orbit LEO constellation, the multi-GNSS visible satellites will increase by 5 to 8 at all latitudes, while the GDOP will be reduced by 6.2% on average. Adding 7-QZSS and 11-NavIC to the four-GNSS-NG, 37.51 to 71.58 satellites are available on global scales. The average position DOP (PDOP), horizontal DOP (HDOP), vertical DOP (VDOP), and time DOP (TDOP) are reduced to 0.82, 0.46, 0.67 and 0.44, respectively.

A Differentiable Extended Kalman Filter for Object Tracking Under Sliding Regime

Tactile sensing represents a valuable source of information in robotics for perception of the state of objects and their properties. Modern soft tactile sensors allow perceiving orthogonal forces and, in some cases, relative motions along the surface of the object. Detecting and measuring this kind of lateral motion is fundamental to react to possibly uncontrolled slipping and sliding of the object being manipulated. Object slip detection and prediction have been extensively studied in the robotic community leading to solutions with good accuracy and suitable for closed-loop grip stabilization. However, algorithms for object perception, such as in-hand object pose estimation and tracking algorithms, often assume no relative motion between the object and the hand and rarely consider the problem of tracking the pose of the object subjected to slipping and sliding motions. In this work, we propose a differentiable Extended Kalman filter that can be trained to track the position and the velocity of an object under translational sliding regime from tactile observations alone. Experiments with several objects, carried out on the iCub humanoid robot platform, show that the proposed approach allows achieving an average position tracking error in the order of 0.6 cm, and that the provided estimate of the object state can be used to take control decisions using tactile feedback alone. A video of the experiments is available as Supplementary Material.

Accuracy Assessment of Atlas L-band GNSS Global Correction Service and Autonomous Positioning at Perlis, Malaysia

Differential Global Navigation Satellite System (DGNSS) is the most common positioning method used for navigation in the hydrography field. During the loss of the correction signal, the differential solution becomes an autonomous solution that may affect the accuracy of the position during that time. However, the availability of the Atlas L-band global correction service that adapts the Real-Time Precise Point Positioning (RT-PPP) technique has broadened the choice of solutions that can be used for navigation in the maritime industry and may solve the problem of signal loss. This research compares the positioning between autonomous solution GNSS and Atlas L-band correction solution using the static method to assess the accuracy of positioning between both methods. Data acquisition of the autonomous positioning and Atlas L-band service was conducted by using Hemisphere receiver VS330 and antenna A43. The statistical T-test reveals that the accuracy of analysis Atlas-L band and autonomous solution GNSS using static positioning was significant, as the p < 0.05 with 95% confidence interval. Besides, the result also shows that the position given by the Atlas L-band is more accurate and precise than Autonomous Solution GNSS, with an average position of 0.479 meters and 2.281 meters, respectively. Ultimately, the continuity of positioning data given by the Atlas L-band in the northern part of Malaysia is good, and positioning using Atlas L-band can be classified as Special Order based on the classification table by the International Hydrographic Organisation (IHO). Keywords: Atlas L-Band, GNSS, RT-PPP, Autonomous Positioning

Characterization of Monochromatic Aberrated Metalenses in Terms of Intensity-Based Moments

Consistent with wave-optics simulations of metasurfaces, aberrations of metalenses should also be described in terms of wave optics and not ray tracing. In this respect, we have shown, through extensive numerical simulations, that intensity-based moments and the associated parameters defined in terms of them (average position, spatial extent, skewness and kurtosis) adequately capture changes in beam shapes induced by aberrations of a metalens with a hyperbolic phase profile. We have studied axial illumination, in which phase-discretization induced aberrations exist, as well as non-axial illumination, when coma could also appear. Our results allow the identification of the parameters most prone to induce changes in the beam shape for metalenses that impart on an incident electromagnetic field a step-like approximation of an ideal phase profile.

Development of interface for kinematic analysis of a delta-type parallel robot

The development and implementation process of a computer interface for the kinematic analysis of a parallel robot, in delta configuration, and its application to a previously formed prototype are exposed. Being identified the associated equations, and deduced the respective geometric parameters. On the other hand, the synthesis of the direct and inverse kinematic models, with the Matlab software, guarantees the calculation of a specific Cartesian position, in the end effector of the robot used, once certain joint values have been assigned to it, or vice versa. Finally, a user-friendly graphical interface is created, whose functions are: data entry, resolution of the models described, issuance of the corresponding results, representation of the robot used and its physical manipulation. The results obtained in the real location of the end effector with respect to the values deduced by the interface, are competitive for both models analyzed, even though the prototype used operates by means of servomotors. An average position error of 0.083 cm per axis and overall of 0.006 cm is observed during the tests developed.

Moving Vehicle Tracking with a Moving Drone Based on Track Association

The drone has played an important role in security and surveillance. However, due to the limited computing power and energy resources, more efficient systems are required for surveillance tasks. In this paper, we address detection and tracking of moving vehicles with a small drone. A moving object detection scheme has been developed based on frame registration and subtraction followed by morphological filtering and false alarm removing. The center position of the detected object area is the input to the tracking target as a measurement. The Kalman filter estimates the position and velocity of the target based on the measurement nearest to the state prediction. We propose a new data association scheme for multiple measurements on a single target. This track association method consists of the hypothesis testing between two tracks and track fusion through track selection and termination. We reduce redundant tracks on the same target and maintain the track with the least estimation error. In the experiment, drones flying at an altitude of 150 m captured two videos in an urban environment. There are a total of 9 and 23 moving vehicles in each video; the detection rates are 92% and 89%, respectively. The number of valid tracks is significantly reduced from 13 to 10 and 56 to 26 in the first and the second video, respectively. In the first video, the average position RMSE of two merged tracks are improved by 83.6% when only the fused states are considered. In the second video, the average position and velocity RMSE are 1.21 m and 1.97 m/s, showing the robustness of the proposed system.

Position preference of essential genes in prokaryotic operons

Essential genes, which form the basis of life activities, are crucial for the survival of organisms. Essential genes tend to be located in operons, but how they are distributed in operons is still unclear for most prokaryotes. In order to clarify the general rule of position preference of essential genes in operons, an index of the average position of genes in an operon was proposed, and the distributions of essential and non-essential genes in operons in 51 bacterial genomes and two archaeal genomes were analyzed based on this new index. Consequently, essential genes were found to preferentially occupy the front positions of the operons, which tend to be expressed at higher levels.