scholarly journals Extraction of Preview Elevation Information Based on Terrain Mapping and Trajectory Prediction in Real-Time

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 76618-76631 ◽  
Author(s):  
Lili Wang ◽  
Dingxuan Zhao ◽  
Tao Ni ◽  
Shuang Liu
Keyword(s):  
Real Time ◽  
Terrain Mapping ◽  
Trajectory Prediction

scholarly journals Moving Time UCAV Maneuver Decision Based on the Dynamic Relational Weight Algorithm and Trajectory Prediction

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Xie Lei ◽  
Ding Dali ◽  
Wei Zhenglei ◽  
Xi Zhifei ◽  
Tang Andi
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Prediction Accuracy ◽  
Control Variable ◽  
Trajectory Prediction ◽  
Constant Weight ◽  
Adaptive Boosting ◽  
Time Performance ◽  
Correlation Degree ◽  
Air Combat

To improve the accuracy and real-time performance of autonomous decision-making by the unmanned combat aerial vehicle (UCAV), a decision-making method combining the dynamic relational weight algorithm and moving time strategy is proposed, and trajectory prediction is added to maneuver decision-making. Considering the lack of continuity and diversity of air combat situation reflected by the constant weight in situation assessment, a dynamic relational weight algorithm is proposed to establish an air combat situation system and adjust the weight according to the current situation. Based on the dominance function, this method calculates the correlation degree of each subsituation and the total situation. According to the priority principle and information entropy theory, the hierarchical fitting function is proposed, the association expectation is calculated by using if-then rules, and the weight is dynamically adjusted. In trajectory prediction, the online sliding input module is introduced, and the long- and short-term memory (LSTM) network is used for real-time prediction. To further improve the prediction accuracy, the adaptive boosting (Ada) method is used to build the outer frame and compare with three traditional prediction networks. The results show that the prediction accuracy of Ada-LSTM is better. In the decision-making method, the moving time optimization strategy is adopted. To solve the problem of timeliness and optimization, each control variable is divided into 9 gradients, and there are 729 control schemes in the control sequence. Through contrast pursuit simulation experiments, it is verified that the maneuver decision method combining the dynamic relational weight algorithm and moving time strategy has a better accuracy and real-time performance. In the case of using prediction and not using prediction, the adaptive countermeasure simulation is carried out with the current more advanced Bayesian inference maneuvering decision-making scheme. The results show that the UCAV maneuvering decision-making ability combined with accurate prediction is better.

Real-time UAV Trajectory Prediction for Safety Monitoring in Low-Altitude Airspace

2019 ◽  
Author(s):  
Matteo Corbetta ◽  
Portia Banerjee ◽  
Wendy Okolo ◽  
George Gorospe ◽  
Dmitry G. Luchinsky
Keyword(s):  
Real Time ◽  
Safety Monitoring ◽  
Trajectory Prediction ◽  
Low Altitude

Multi-Model and Learning-Based Framework for Real-Time Trajectory Prediction

2020 ◽  
Author(s):  
Abdelmoudjib Benterki ◽  
Vincent Judalet ◽  
Choubeila Maaoui ◽  
Moussa Boukhnifer
Keyword(s):  
Real Time ◽  
Trajectory Prediction

Master-Slave Control Technology Research for Abdominal Minimally Invasive Surgery Robot

2010 ◽  
Author(s):  
Yili Fu ◽  
Han Li ◽  
Qi Xie
Keyword(s):  
Minimally Invasive ◽  
Real Time ◽  
Robot Control ◽  
Transformation Method ◽  
Feedback Mechanism ◽  
Surgical Robot ◽  
Pci Bus ◽  
Trajectory Prediction ◽  
A Algorithm ◽  
The Impact

According to characteristics of abdominal minimally invasive robotic surgical tasks, based on performant industrial computer platform, an extended multifunctional hardware communicates with PCI-bus is designed, a master-slave control system is studied. In order to solve the problem of low responsivity caused by traditional inverse kinematics transformation method, a algorithm based on equivalent differential transformation suitable for real-time master-slave surgical robot control is put forward, and the accumulated error of the algorithm is eliminated by feedback mechanism. A fast trajectory planning method efficient in real-time master-slave surgical robot control is put forward to replace traditional trajectory prediction and off-line calculation. Finally, in order to avoid the impact on the accuracy of the system coursed by hand-trembling of operators, a digital filter is designed to help filtering the master manipulator signal.

scholarly journals A Real-Time Trajectory Prediction Method of Small-Scale Quadrotors Based on GPS Data and Neural Network

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7061
Author(s):  
Zhao Yang ◽  
Rong Tang ◽  
Jie Bao ◽  
Jiahuan Lu ◽  
Zhijie Zhang
Keyword(s):  
Real Time ◽  
Stable State ◽  
Prediction Method ◽  
Small Scale ◽  
Trajectory Data ◽  
Trajectory Prediction ◽  
Unit Model ◽  
Proposed Model ◽  
Historical Trajectory ◽  
Gated Recurrent Unit

This paper proposes a real-time trajectory prediction method for quadrotors based on a bidirectional gated recurrent unit model. Historical trajectory data of ten types of quadrotors were obtained. The bidirectional gated recurrent units were constructed and utilized to learn the historic data. The prediction results were compared with the traditional gated recurrent unit method to test its prediction performance. The efficiency of the proposed algorithm was investigated by comparing the training loss and training time. The results over the testing datasets showed that the proposed model produced better prediction results than the baseline models for all scenarios of the testing datasets. It was also found that the proposed model can converge to a stable state faster than the traditional gated recurrent unit model. Moreover, various types of training samples were applied and compared. With the same randomly selected test datasets, the performance of the prediction model can be improved by selecting the historical trajectory samples of the quadrotors close to the weight or volume of the target quadrotor for training. In addition, the performance of stable trajectory samples is significantly better than that with unstable trajectory segments with a frequent change of speed and direction with large angles.

Sign in / Sign up

Export Citation Format

Share Document