Review and classification of trajectory summarisation algorithms: From compression to segmentation

With the continuous development and cost reduction of positioning and tracking technologies, a large amount of trajectories are being exploited in multiple domains for knowledge extraction. A trajectory is formed by a large number of measurements, where many of them are unnecessary to describe the actual trajectory of the vehicle, or even harmful due to sensor noise. This not only consumes large amounts of memory, but also makes the extracting knowledge process more difficult. Trajectory summarisation techniques can solve this problem, generating a smaller and more manageable representation and even semantic segments. In this comprehensive review, we explain and classify techniques for the summarisation of trajectories according to their search strategy and point evaluation criteria, describing connections with the line simplification problem. We also explain several special concepts in trajectory summarisation problem. Finally, we outline the recent trends and best practices to continue the research in next summarisation algorithms.

Controlled deep perforation by radial drilling of channels with the "Perfobur" technical system to intensify the reservoir inflow

The paper presents a technology for controlled deep penetrating perforation using the Perfobur technical system to intensify inflow by drilling radial channels 69 mm in diameter, up to 25 metres in length. This technology was first applied to a carbonate reservoir in the Bashkirian tier, characterised by high heterogeneity and close proximity of bedrock water. An adjacent well, close to the acid fracture well, with identical reservoir properties, was selected. Well "A" was acid fractured and well "B" was drilled using Perfobur technology with two directional channels, each 14 metres in length. In well "B", after drilling the channels, hydrochloric acid solution was injected through a special hydromonitor nozzle at two points. A total of 48 m3 of acid was injected into the "B" well. Comparing the results of well "B" with the well where the hydrofracturing was performed allow speaking about high efficiency of the controlled radial drilling technology. The ability to predict the channel trajectory, knowledge of its actual trajectory in combination with acid treatment of the reservoir using hydromonitor nozzle at a considerable distance from the reservoir allows achieving a significant increase in oil flow rate with lower water cut of the produced oil.

Exploring the Optimal Design for and Experimentation on a Bowl-Based Mechanism for Transplanting Potted Strawberry Seedlings

To improve the mechanization of strawberry planting integration and the efficiency of fetching and transplanting seedlings, an integrated transplanting mechanism with protruding, fetching and planting is designed. This new device can realize rapid fetching and pushing bowl movements. The working principle of the slewing mechanism is analyzed, a kinematics model of the mechanism is established, and the optimization goal is established. Visual auxiliary analysis software is developed, optimized parameters are established, and the corresponding theoretical trajectory is provided. A three-dimensional model is established and a virtual simulation design analysis is performed to obtain a simulation trajectory. Three-dimensional printing technology is used to manufacture the test prototype, and the actual working trajectory of the test prototype is extracted using high-speed photography technology, which verifies the consistency of the actual trajectory with the theoretical and simulated trajectories. A prototype transplanting experiment is performed, showing that the success rate of seedling extraction is 91.2% and the rate of excellent planting is 82.8%, which meet the requirements for integrated strawberry harvesting, planting and transplanting and verify the correctness and feasibility of the mechanism design.

Individual navigation templates for the installation of pedicle screws in the cervical spine

The experiment was performed on 2 samples of the pig's cervical spine. 12 transpedicular screws were implanted using navigation templates. The safety and accuracy of installation of screws were evaluated by analyzing the results of computed tomography. 12 screws had a level of implantation safety of 0 degree – the screw was completely inside the bone structures of the vertebra. The accuracy of the implanted screws was evaluated by determining the degree of deviation of the obtained screw trajectory from the planned one. The resulting accuracy of the installed screws is 91 % and corresponds to class 1. At standard deviation, there were no significant differences in the axial and sagittal angles between the planned installation and the actual trajectory of the screw for the subaxial cervical spine on the left and right. There were no significant differences in the standard deviation in the axial projection at the points of entry and intended exit of the screw. Statistical analysis did not reveal significant differences between planned and actual results (P > 0.05).

Predicting Ship Trajectory Based on Neural Networks Using AIS Data

To create an autonomously moving vessel, it is necessary to know exactly how to determine the current coordinates of the vessel in the selected coordinate system, determine the actual trajectory of the vessel, estimate the motion trend to predict the current coordinates, and calculate the course correction to return to the line of the specified path. The navigational and hydrographic conditions of navigation on each section of the route determine the requirements for the accuracy of observations and the time spent on locating the vessel. The problem of predicting the trajectory of the vessel's motion in automatic mode is especially important for river vessels or river-sea vessels, predicting the trajectory of the route sections during the maneuvering of the vessel. At the moment, one of the most accurate ways of determining the coordinates of the vessel is by reading the satellite signal. However, when a vessel is near hydraulic structures, problems may arise connected with obtaining a satellite signal due to interference and, therefore, the error in measuring the coordinates of the vessel increases. The likelihood of collisions and various kinds of incidents increases. In such cases, it is possible to correct the trajectory of the movement using an autonomous navigation system. In this work, opportunities of the possible application of artificial neural networks to create such a corrective system using only the coordinates of the ship's position are discussed. It was found that this is possible on sections of the route where the ship does not maneuver.

Repetitive Control for Multi-Joint Arm Movements Based on Virtual Trajectories

According to the neuromuscular model of virtual trajectory control, the postures and movements of limbs are performed by shifting the equilibrium positions determined by agonist and antagonist muscle activities. In this study, we develop virtual trajectory control for the reaching movements of a multi-joint arm, introducing a proportional-derivative feedback control scheme. In virtual trajectory control, it is crucial to design a suitable virtual trajectory such that the desired trajectory can be realized. To this end, we propose an algorithm for updating virtual trajectories in repetitive control, which can be regarded as a Newton-like method in a function space. In our repetitive control, the virtual trajectory is corrected without explicit calculation of the arm dynamics, and the actual trajectory converges to the desired trajectory. Using computer simulations, we assessed the proposed repetitive control for the trajectory tracking of a two-link arm. Our results confirmed that when the feedback gains were reasonably high and the sampling time was sufficiently small, the virtual trajectory was adequately updated, and the desired trajectory was almost achieved within approximately 10 iterative trials. We also propose a method for modifying the virtual trajectory to ensure that the formation of the actual trajectory is identical even when the feedback gains are changed. This modification method makes it possible to execute flexible control, in which the feedback gains are effectively altered according to motion tasks.

UB-LSTM: A Trajectory Prediction Method Combined with Vehicle Behavior Recognition

In order to make an accurate prediction of vehicle trajectory in a dynamic environment, a Unidirectional and Bidirectional LSTM (UB-LSTM) vehicle trajectory prediction model combined with behavior recognition is proposed, and then an acceleration trajectory optimization algorithm is proposed. Firstly, the interactive information with the surrounding vehicles is obtained by calculation, then the vehicle behavior recognition model is established by using LSTM, and the vehicle information is input into the behavior recognition model to identify vehicle behavior. Then, the trajectory prediction model is established based on Unidirectional and Bidirectional LSTM, and the identified vehicle behavior and the input information of the behavior recognition model are input into the trajectory prediction model to predict the horizontal and vertical speed and coordinates of the vehicle in the next 3 seconds. Experiments are carried out with NGSIM data sets, and the experimental results show that the mean square error (MSE) between the predicted trajectory and the actual trajectory obtained by this method is 0.124, which is 97.2% lower than that of the method that does not consider vehicle behavior and directly predicts the trajectory. The test loss is 0.000497, which is 95.68% lower than that without considering vehicle behavior. The predicted trajectory is obviously optimized, closer to the actual trajectory, and the performance is more stable.

Analysis and Optimization of Interpolation Points for Quadruped Robots Joint Trajectory

Trajectory planning is the foundation of locomotion control for quadruped robots. This paper proposes a bionic foot-end trajectory which can adapt to many kinds of terrains and gaits based on the idea of trajectory planning combining Cartesian space with joint space. Trajectory points are picked for inverse kinematics solution, and then quintic polynomials are used to plan joint space trajectories. In order to ensure that the foot-end trajectory generated by the joint trajectory planning is closer to the original Cartesian trajectory, the distributions of the interpolation point are analyzed from the spatial domain to temporal domain. An evaluation function was established to assess the closeness degree between the actual trajectory and the original curve. Subsequently, the particle swarm optimization (PSO) algorithm and genetic algorithm (GA) for the points selection are used to obtain a more precise trajectory. Simulation and physical prototype experiments were included to support the correctness and effectiveness of the algorithms and the conclusions.

Active rectifying control of vehicle with tire blowout based on adaptive fuzzy proportional–integral–derivative control

To avoid casualties and economic loss caused by vehicle yawing motion during the tire blowout, first, by changing several key parameters of the characteristics, this article uses CarSim software and MATLAB/Simulink to establish a vehicle model of tire blowout based on the UniTire model. This model is implemented to simulate tire blowout caused by the change of the vehicle motion state. Second, considering the driver error and radical-operated steering wheel after tire blowout leads to runaway car problems. This article takes the target trajectory and actual trajectory of error and error rate as the system input; an adaptive fuzzy proportional–integral–derivative controller is designed to determine the vehicle steering wheel angle during the tire blowout and replace the driver to control the direction of the vehicle. The results indicate that the designed controller is capable of ensuring the vehicle constancy and keeping the vehicle on the original track.

Studies and simulations on the flight trajectories of spinning table tennis ball via high-speed camera vision tracking system

When a table tennis ball is hit by a racket, the ball spins and undergoes a complex trajectory in the air. In this article, a model of a spinning ball is proposed for simulating and predicting the ball flight trajectory including the topspin, backspin, rightward spin, leftward spin, and combined spin. The actual trajectory and rotational motion of a flying ball are captured by three high-speed cameras and then reconstructed using a modified vision tracking algorithm. For the purpose of model validation, the simulated trajectory is compared to the reconstructed trajectory, resulting in a deviation of only 2.42%. Such high modeling accuracy makes this proposed method an ideal tool for developing the virtual vision systems emulating the games that can be used to train table tennis players efficiently.