Abstract
The ability to recognize motions is an important feature in cutting-edge robotics or autonomous systems, such as self-driving cars, humanoid robots, and human-robot interactions, resulting in improved safety and efficiency. Addressing this critical issue, we introduce a simple framework leveraging the benefits of the normalized real-time network traffic data of the middleware ROS platform formulated in the form of RGB or grayscale images to train the Convolutional Neural Network (CNN) system in order to learn the motion pattern of the robot. For our experimental platform, we employ the GVR-BOT Unmanned Ground Vehicle (UGV), developed by the U.S. Army Combat Capabilities Development Command (CCDC), Ground Vehicle Systems Center (GVSC). We rigorously study the performance of our motion recognition system under several different lengths of data (epochs). In addition, we compare the relative merits of our proposed system with respect to the performance of the well-known ‘Bag-of-Features’ (BoFs) detection algorithm widely implemented in computer vision. Our research indicates the efficacy of the proposed motion recognition system as we can achieve a reasonably high detection accuracy ≥ 0.97 within a minimum detection time of two epochs highlighting its real-time benefits. Overall, our recognition system can also achieve superior detection performance compared to the efficacy of the BoFs algorithm.
Original language | English |
---|---|
Title of host publication | 2024 International Joint Conference on Neural Networks, IJCNN 2024 - Proceedings |
Place of Publication | Japan |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 1-8 |
ISBN (Electronic) | 9798350359312 |
ISBN (Print) | 9798350359329 |
DOIs | |
Publication status | Published - 30 Jun 2024 |
Event | International Joint Conference on Neural Networks (IJCNN) 2024 - PACIFICO Yokohama, Yokohama, Japan Duration: 30 Jun 2024 → 05 Jul 2024 https://2024.ieeewcci.org/ https://confcats-siteplex.s3.us-east-1.amazonaws.com/wcci24/IEEE_WCCI_2024_Program_d597587f62.pdf (Program) https://ieeexplore.ieee.org/xpl/conhome/10649807/proceeding (Proceedings) https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10650734 (Front matter) |
Publication series
Name | Proceedings of the International Joint Conference on Neural Networks |
---|
Conference
Conference | International Joint Conference on Neural Networks (IJCNN) 2024 |
---|---|
Country/Territory | Japan |
City | Yokohama |
Period | 30/06/24 → 05/07/24 |
Other | IEEE WCCI 2024 is the world’s largest technical event on computational intelligence, featuring the three flagship conferences of the IEEE Computational Intelligence Society (CIS) under one roof: The International Joint Conference on Neural Networks (IJCNN), the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) and the IEEE Congress on Evolutionary Computation (IEEE CEC). |
Internet address |