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Robotics and Autonomous Systems Chapter 4 Inside a sprawling distribution warehouse, an autonomous mobile robot relies on multiple sensors for navigation. However, when it encounters featureless aisles where visual landmarks disappear, navigating becomes challenging. Analog Devices' ADIS1657x inertial measurement unit steps in, providing precise orientation and positioning data to ensure the robot maintains accuracy and confidence even without external references. This inertial sensor exemplifies how robust sensor fusion enables robots to operate reliably in complex industrial settings. Industrial automation is progressing, with robotics and autonomous machines at the forefront. As companies encounter persistent labor shortages, increasing costs, and a need for more flexible manufacturing, they are turning to robotic systems to remain competitive. Robotics Revolution in Industrial Settings While traditional industrial robots have long been utilized for tasks such as welding, assembly, and material handling, recent advancements in robotics are pushing the boundaries even further. Humanoid robots and mobile autonomous robots (AMRs) can now adapt to dynamic, unstructured environments, creating new possibilities for automation. Humanoid robots, in particular, are emerging in factories designed around human workflows. Rather than incurring the high costs of facility retooling, these robots can take on physically demanding and repetitive logistics, warehousing, and maintenance tasks. Meanwhile, AMRs and autonomous industrial vehicles are revolutionizing material transport and inventory management by safely navigating complex layouts and collaborating alongside human employees. Inertial Sensors for Robotic Applications Driving this robotics transformation are high- performance inertial sensors. With enhanced precision, reduced noise, and increased miniaturization, these sensors facilitate better navigation, balance, and motion control without depending solely on external references. This enables robots to function safely, adaptively, and efficiently in dynamic industrial environments. However, creating these complex robotic systems presents its own set of challenges. Optimizing inherent sensor parameters limited by design and physics, such as noise, vibration susceptibility, and hysteresis, can be a time-intensive process. To streamline development, fully calibrated sensor modules that correct biases, sensitivity, temperature codes, and axial alignment are available, offering an out-of-the- box subsystem that enhances time-to-market. 12 Engineering Reliable Industrial Automation With Sensor Fusion