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10 | The Future of Robotics Texas Instruments Figure 3: Sensor fusion helps achieve its goal by obtaining better insights from data. (Source: Werayuth Tes/Shutterstock.com). Data Correlation One of the first things that must be determined when data comes in is correlation. Think back to our dessert. We were focused on that when talking about it. All our data was correlated; that is, we only discussed data that was about the dessert itself. Correlated data is data in relationship with the object under analysis. But what would happen if, while getting my dessert, the fire alarm went off? The fire alarm is a new bit of data. It has nothing to do with the desert and whether I should consume it. However, this latest bit of data is essential. I need to take action and respond to the fire alarm. It is a high priority. Similarly, uncorrelated data is data coming into the autonomous robotic system that is not necessarily to the main point under analysis in its current operation, yet it is relevant. It is not directly related to the current process, but it requires that subsequent steps (planning and action) must be considered. Sensor Fusion Objectives The goal of Sensor Fusion is to gain better insights from data. Let's now pivot to examine four ways sensor fusion works to enable the reality of better insights for autonomous robotic systems. (Figure 3). Increased Quality of the Data Sensor fusion technology enables the system to operate with better quality data. What do we mean by this? The data itself has not changed. Take the issue of electronic noise. Specifically, I am referring to noise inherent in measurements, the variability inherent in sensory data due to a wide variety of factors. Noise can be reduced by employing more sensors and then performing mathematical or software filtering functions to achieve a more specific data set. Mathematical averaging functions can be employed. Different sensors could be used in combination, and the results compared and used to reduce uncertainty. Texas Instruments Ultrasonic Sensing Solutions Texas Instruments is the sensor fusion solution provider of choice. A key technology taking advantage of sensor fusion is ultrasonic sensing. Texas Instruments is a leader at delivering products for ultrasonic sensing. Ultrasonic sensors can detect sound waves at a frequency above the upper limit of human hearing, which is approximately 20kHz. Ultrasonic sensors are commonly employed to detect objects by listening for the echoes that reflect from any obstacles. Autonomous robotic systems commonly employ ultrasonic sensors for collision avoidance. Ultrasonic sensing might be used in combination with other sensors such as mmWave, camera, and Light Detection and Ranging (LiDAR). Ultrasonic sensing is characterized by short detection range, wide detection angle, good resolution range, the ability to perform well in bad weather. Ultrasonic sensing is a low-cost, slower-speed alternative to radar for robots that don't need to reach high speeds in homes and factories. Ultrasonic sensing is more reliable than optical time-of-flight (ToF) sensing for obstacle avoidance, as ultrasonic sensing is not affected by the amount of available light reflected off of obstacles. Another benefit of ultrasonic sensing is its ability to sense glass or any other transparent surface since it uses sound waves instead of light to detect objects. Ultrasonic sensing is a low-cost, slower-speed alternative to radar for robots that don't need to reach high speeds in homes and factories. " "