8.10. Future Trends

• AI-based sensor fusion

AI-based sensor fusion refers to the process of using artificial intelligence techniques to combine data from different sensors. This helps in creating a more accurate and reliable understanding of the environment. AI can analyze sensor data from various sources, such as cameras and radar, to detect objects or identify conditions more effectively than using a single sensor input alone.

Imagine a smart car using several sensors to navigate. The car's AI takes inputs from cameras, ultrasonic sensors, and GPS to create a comprehensive view of its surroundings. Like how a person uses multiple senses to better understand their environment, this fusion of sensor data helps the car recognize obstacles and make safe driving decisions.

• Smart actuators with built-in sensors

Smart actuators are devices that not only provide motion but also have integrated sensors to monitor feedback from their operations. By having built-in sensors, these actuators can assess their performance in real-time and make adjustments without needing external controllers. This leads to more efficient and responsive robotic systems.

Think of an automatic door closer that not only closes doors but also has sensors to detect the door's speed and position. If the actuator senses that the door is closing too quickly, it can automatically slow down to ensure smooth operation, just like how a smart thermostat adjusts the heating based on its temperature sensor readings.

• Edge computing for faster sensor-actuator loops

Edge computing involves processing data near the source of generation instead of relying on a centralized cloud system. In the context of robotics, edge computing allows sensor data to be processed in real-time at the location where it is collected. This significantly reduces latency, resulting in faster communication between sensors and actuators and enabling more immediate responses.

Imagine a restaurant that uses a digital order system. Instead of sending all orders to a central kitchen far away (which takes time), the system allows chefs in each area of the restaurant to receive orders instantly and locally. This is similar to how edge computing enables robotic systems to react promptly and accurately by handling data at the local machine level.

• Integration with BIM (Building Information Modeling) for construction robotics

Building Information Modeling (BIM) is a digital representation of the physical and functional characteristics of a facility. By integrating robotic systems with BIM, robots can receive precise instructions directly from a digital model of a construction site. This integration allows for greater accuracy and efficiency in tasks like building or monitoring structures.

Think of an architect using a detailed blueprint to instruct builders on how to construct a house. In this analogy, the robots are like builders that take instructions from a digital blueprint provided by BIM. So, just as a builder follows blueprints to ensure accuracy, robots utilize BIM data for executing construction tasks correctly.

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