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The integration of emergent technologies such as AI and ML in robotics has widened the scope of robotics applications, leading to the automation of various processes across different sectors.
FREMONT, CA: The integration of artificial intelligence (AI) and machine learning (ML) has enabled organizations to deploy robots for various processes, driving autonomy and efficiency. The capabilities of AI-powered robots have revolutionized the processes across multiple sectors, ranging from manufacturing to retail. However, the implementation of robotics is pronounced in some areas more than others.
Law enforcement agencies across the world have started leveraging robotics applications in hazardous situations. For instance, specialized robots with the capability of assessing threats using sensor technology and monitoring equipment are being deployed for bomb disposal operations. Also, emergency response agencies are utilizing robots to navigating burning buildings and unstable structures. The mobile units are continuously evolving with enhanced sensors, user interfaces, and other capabilities, enabling better emergency response.
One of the primary requirements of surgeons is a pair of steady heads, as even the tiniest movement in the wrong direction could lead to the severing of arteries, tissues, or organs. Although robotics technology has not evolved enough to produce fully autonomous surgeons, many AI-powered robotics systems have been developed to augment the capabilities of human surgeons. Some robotics equipment integrates the emerging technologies with advanced software to enable remote operations with utmost accuracy.
Several construction agencies are leveraging robot welders to conduct precise welds, offering better accuracy than the most experienced human welders, whose precision is often hindered by the heavy welding and face protection gear. Also, the labor shortage in the construction sector, especially in welding, has spurred organizations to turn toward robotics applications. Robotics welders are already utilized in automotive manufacturing industries, and it will not be long before their implementation becomes as common in the construction industry.
Agricultural productivity depends on a multitude of conditions, including weather, soil, pests, weeds, labor, and energy. Over the years, the emerging technology has revolutionized the agricultural sector, leading to the introduction of sophisticated machinery able to conduct autonomous functions such as seeding, weeding, and harvesting, among other things. The integration of robotics, drone technology, and machine learning techniques has aided tech-savvy farmers to increase their yield through precision agriculture, promoting efficiency as well as productivity.
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