Issue link: https://resources.mouser.com/i/1442859
16 | The Future of Robotics Texas Instruments Figure 5: Robots of the future will be more interactive with humans. Figure 7: TI IWR mmWave sensors processing chain. Figure 6: Robotic arm with a physical safety cage. Safety guards around robotic arms As robots interact more with humans—either in service capacities or in flexible, low-quantity batch- processing automation tasks—it is critical that they do not cause harm to the people with whom they interact, as shown in Figure 5. Historically, the common method is to create a safety curtain or keep-out zone around the robot's field of operation to ensure physical separation, as shown in Figure 6. Sensors make it possible for a virtual safety curtain or bubble to separate robotic operation from unplanned human interaction, and to avoid robot-to-robot collision as density and operation programmability increase. Vision-based safety systems require controlled lighting, which increase energy consumption, generate heat and require maintenance. In dusty manufacturing environments such as textile or carpeting, lenses need frequent cleaning and attention. Because mmWave sensors are robust, detecting objects regardless of lighting, humidity, smoke and dust on the factory floor, they are well suited to replace vision systems, and can provide this detection with very low processing latency— typically under 2ms. With a wide field of view and long detection range, mounting these sensors above the area of operation simplifies installation. The ability to detect multiple objects or humans with only one mmWave sensor reduces the number of sensors required and reduces cost. Point-cloud information generated by mmWave sensors mmWave radar sensors convert radio frequency (RF) front-end analog data to a digital representation through an analog-to-digital converter. This digitally converted data requires high-speed external data buses to bring the data stream to the processing chain, where a series of mathematical operations generate the range, velocity, and angular information for points detected in the sensor's field of view. Because these systems are traditionally large and expensive, TI sought to integrate all of this functionality onto a single monolithic piece of CMOS silicon, thus reducing size, cost and power consumption. The additional digital processing resources now handle data post-processing for such tasks as clustering, tracking and classification, as shown in Figure 7.