Artificial Intelligence for Enhanced Autonomy in Robotics vision for object recognition and tracking using sensor integration for situational awareness
Year: 2025
Type: article
Abstract: This paper reviews the current state of artificial intelligence (AI) in robotics, focusing on its applications, challenges, and future directions. We discuss the role of machine learning, computer vision, and sensor integration in enabling autonomous robots to perceive, reason, and act in complex environments. Artificial Intelligence for Enhanced Autonomy in Robotics: Computer Vision for Object Recognition and Tracking, and Sensor Integration for Situational Awareness, Computer Vision for Object Recognition and Tracking,1. Object detection: Using techniques like YOLO (You Only Look Once) or SSD (Single Shot Detector) to detect objects in images or video streams, Object tracking: Using techniques like Kalman filter or particle filter to track objects across frames, Deep learning-based approaches: Using convolutional neural networks (CNNs) to recognize and classify objects.
Author: Dr ASHOK KUMAR RAMADOSS
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6930666272
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