scholarly journals Automatic Manipulator Tracking Control Based on Moving Target Trajectory Prediction

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Haifeng Luo
Keyword(s):  
Target Tracking ◽  
Tracking Control ◽  
Moving Target ◽  
Trajectory Prediction ◽  
Target Trajectory ◽  
Proposed Model ◽  
Core Issue ◽  
Testing Algorithm ◽  
The Given ◽  
Automatic Manipulator

The core issue of automatic manipulator tracking control is how to ensure the given moving target follows the expected trajectory and adapts to various uncertain factors. However, the existing moving target trajectory prediction methods rely on highly complex and accurate models, lacking the ability to generalize different automatic manipulator tracking scenarios. Therefore, this study tries to find a way to realize automatic manipulator tracking control based on moving target trajectory prediction. In particular, a moving target trajectory prediction model was established, and its parameters were optimized. Next, a tracking-training-testing algorithm was proposed for manipulator’s automatic moving target tracking, and the operating flows were detailed for training module, target detection module, and target tracking module. The proposed model and algorithm were proved effective through experiments.

An Improved Trace Method for Moving Target under Occlusion

2014 ◽  
Vol 672-674 ◽  
pp. 1931-1934
Author(s):  
Yu Bing Dong ◽  
Guang Liang Cheng ◽  
Ming Jing Li
Keyword(s):  
Mathematical Model ◽  
Target Tracking ◽  
Difficult Problem ◽  
Block Matching ◽  
Experimental Results ◽  
Polar Coordinates ◽  
Moving Target ◽  
Trajectory Prediction ◽  
Tracking Method

Occlusion is a difficult problem to be solved in the process of target tracking. In order to solve the problem of occlusion, a new tracking method combined with trajectory prediction and multi-block matching is presented and studied,and a mathematical model of trajectory prediction of moving target is established in polar coordinates and verified through some experiments. The experimental results show that the new tracking method can be better to trace and forecast the moving target under occlusion.

scholarly journals Augmented Intention Model for Next-Location Prediction from Graphical Trajectory Context

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Canghong Jin ◽  
Zhiwei Lin ◽  
Minghui Wu
Keyword(s):  
State Of The Art ◽  
Real Life ◽  
Traffic Planning ◽  
Trajectory Prediction ◽  
User Intention ◽  
Convolutional Networks ◽  
Proposed Model ◽  
Gated Recurrent Units ◽  
The Given ◽  
Travel Recommendation

Human trajectory prediction is an essential task for various applications such as travel recommendation, location-sensitive advertisement, and traffic planning. Most existing approaches are sequential-model based and produce a prediction by mining behavior patterns. However, the effectiveness of pattern-based methods is not as good as expected in real-life conditions, such as data sparse or data missing. Moreover, due to the technical limitations of sensors or the traffic situation at the given time, people going to the same place may produce different trajectories. Even for people traveling along the same route, the observed transit records are not exactly the same. Therefore trajectories are always diverse, and extracting user intention from trajectories is difficult. In this paper, we propose an augmented-intention recurrent neural network (AI-RNN) model to predict locations in diverse trajectories. We first propose three strategies to generate graph structures to demonstrate travel context and then leverage graph convolutional networks to augment user travel intentions under graph view. Finally, we use gated recurrent units with augmented node vectors to predict human trajectories. We experiment with two representative real-life datasets and evaluate the performance of the proposed model by comparing its results with those of other state-of-the-art models. The results demonstrate that the AI-RNN model outperforms other methods in terms of top-k accuracy, especially in scenarios with low similarity.

Moving Target Tracking Based on Trajectory Prediction

2014 ◽  
Vol 1070-1072 ◽  
pp. 2062-2065
Author(s):  
Yu Bing Dong ◽  
Ying Sun ◽  
Ming Jing Li
Keyword(s):  
Mathematical Model ◽  
Target Tracking ◽  
Tracking System ◽  
Moving Target ◽  
Improved Method ◽  
Trajectory Prediction ◽  
Tracking Method ◽  
Moving Target Tracking

An improved tracking method based on trajectory prediction is proposed and studied. The moving target tracking system is given and described. In order to fast and efficient tracking, a mathematical model of trajectory prediction of moving target is established. A large of experiments are carried by MALTAB. The results show that the improved method is better, improves the tracking speed and tracking precision.

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