An Arrow-Curve Path Planning Model for Mobile Beacon Node Aided Localization in Air Pollution Monitoring System IoT

In wireless sensor networks, it is crucial to support the collected data of sensor nodes with position information. One of the promising ways to acquire the position of unknown nodes is using a mobile anchor node that traverses throughout the network, stops at determined points, and sends its position to aid in obtaining the location of other unknown nodes. The main challenge in using mobile anchor nodes lies in designing the path model with the highest localization accuracy, shortest path length, full coverage area, and minimal power consumption. In this paper, a path model named the Arrow-Curve path model is proposed for mobile node aided localization. The proposed path model can effectively localize all the static unknown sensor positions in the network field with high positioning accuracy and low power consumption while pledging full coverage area. The sensor network is implemented using MATLAB simulation and MCU node in both static unknown nodes and the mobile anchor node. The realtime environment guarantees a realistic environmental model with reliable results. The path model is implemented in realtime in indoor and outdoor environments and compared to the H-Curve path model using a trilateration technique. The results show that the suggested path model achieves better results compared to H-Curve model. The proposed path model achieves an average position error less than that of H-Curve by 10.6% in a simulation environment, 5% in an outdoor realtime environment, and 9% in an indoor realtime environment, and it decreases power consumption by 62.65% in the simulation environment, 50% in the outdoor realtime environment, and 75% in the realtime environment in indoor compared to H-Curve.

Control of Unmanned Surface Vehicle Along the Desired Trajectory Using Improved Line of Sight and Estimated Sideslip Angle

In order to improve the accuracy and robustness of path following control for an Unmanned Surface Vehicle (USV) suffering from unknown and complex disturbances, a variable speed curve path following a control method based on an extended state observer was proposed. Firstly, the effect of the environmental disturbances on the USV is equivalent to an unknown and time-varying sideslip angle, and the sideslip angle is estimated by using the extended state observer (ESO) and compensated in the Line of Sight (LOS) guidance law. Secondly, based on the traditional LOS guidance law, the design of the surge velocity guidance law is added to enable the USV to self-adjust the surge velocity according to the curvature of the curve path, thus further improving the tracking accuracy. Finally, the heading and speed controller of the USV is designed by using a sliding mode control to track the desired heading and speed accurately, and then the path following control of the USV’s curve path is realised. Simulation results verify the effectiveness of the proposed method.

Composite Curve Path following an Underactuated AUV

This paper addresses the problem of composite curve path following for an underactuated autonomous underwater vehicle by utilizing an adaptive integral line-of-sight (AILOS) guidance and nonlinear iterative sliding mode (NISM) controller. First, the composite curve path is parametrized by a common scalar variable in a continuous way. Then, the kinematics error of an underactuated vehicle is described based on the nonprojection Frenet–Serret frame with a virtual point, which can be eliminated by the virtual point control and AILOS guidance. Meanwhile, the subpath switching algorithm is studied to realize the global path following for the composite curve path. Besides, the NISM controller is cascaded with the AILOS guidance law, and the cascade structure proved to be globally κ -exponentially stable under the influence of slow time-varying currents. Finally, simulations are considered to demonstrate the effectiveness of the proposed composite curve path following control scheme.

About Black Holes

All kinds of waves occur for the disturbances in the quiet gravitational field. Different waves powered differently and propagated in the gravitational field. A black hole is the higher GFI (Gravitational Field Intensity) area. The rays do not possess, coming from a distant source when pass by the black holes, adequate strength to disturb in the higher GFI area of the black holes. Naturally, the rays take on a curve path as the provision in a circular area depends on the radius (distance), keeping distance according to the lower GFI area around the black holes’ centre.

Five-Axis Freeform Surface Color Printing Technology Based on Offset Curve Path Planning Method

Great progress has been made in 2D color printing with inkjet technology, and mature related products have come out, but there still exists great developmental space in 3D color printing. Therefore, a new path planning method based on the offset curve for 3D inkjet technology is proposed in this paper. Offset curves are generated on a freeform surface with geodesic equidistance, and then points for color printing are generated along the offset curves. In this paper, the principle of color printing technology with a 5-axis platform and the offset curve path planning (OCPP) method are presented. In addition, comparisons between the OCPP and adaptive filling algorithm based on the section method (AFSM) have been implemented. The OCPP significantly increased the rate of the theoretical filling area from 0.89 to 0.99 on a freeform surface.

Comparison of execution times of Kaedah A for different movement trajectories using Virtual Sensei Lite

The main objective of this study is to compare the execution times produced by fending off techniques of Seni Silat Cekak Malaysia (SSCM), Kaedah A for different movement trajectories. Three kind of movement trajectories for Kaedah A were carried out which were Trajectory A (normal path), Trajectory B (curve path) and Trajectory C (starting by pulling the hand to the back and continue as Trajectory A). The experiments were conducted using motion capture system where the movement position of the left hand during the execution of Kaedah A were recorded by Kinect sensor, prior to storing and processing via Virtual Sensei (VS) Lite software. A total of four (4) experienced practitioners from SSCM with their consent were selected to perform Kaedah A techniques. The data acquired were further analyzed to determine their kinematic characteristics. Results showed that the execution of Kaedah A using Trajectory A produced the shortest time and highest velocity with average of 0.071±0.007s and 6.438±0.863ms-1 respectively, compared to Trajectory B (0.087±0.011s, 5.230±0.578 ms-1) and Trajectory C (0.149±0.015s, 2.903±0.273ms-1). Therefore, Trajectory A is considered to be more efficient than Trajectory B and Trajectory C in terms of execution times and maximum velocity produced by Kaedah A.