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20 | The Future of Robotics Texas Instruments From traditional industrial robotic systems to today's latest collaborative robots (or "cobots"), robots rely on sensors that generate increasingly massive volumes of highly varied data. This data can help build better machine learning (ML) and artificial intelligence (AI) models that robots rely on to become autonomous, making real-time decisions and navigating in dynamic real-world environments. Industrial robots are typically placed in caged environments; a human entering that environment stops robot movement for safety reasons. But limiting human/robot collaboration prevents the realization of many benefits. Robots with autonomous capabilities would enable the safe and productive co-existence of humans and robots. Sensing and intelligent perception in robotic applications are important, because the effective performance of robotic systems–particularly ML/AI systems–greatly depends on the performance of sensors that provide critical data to these systems. Today's wide range of increasingly sophisticated and accurate sensors, combined with systems that can fuse all of this sensor data together, are enabling robots to have increasingly good perception and awareness. How Sensor Data is Powering AI in Robotics Matthieu Chevrier, Systems and Applications Manager, Worldwide Industrial Systems Texas Instruments Next-generation robotics rely on the fusion of sensor data and AI processed at the edge