FEATURE ROBOTICS THE AUTONOMOUS INDUSTRIAL REVOLUTION
high resolution radar systems at reasonable cost. Radar-based digital beamforming enables detection of radial velocity, angle, and distance to multiple targets under the harshest environmental conditions—it’s key for the safe and efficient interaction of robots, cobots, and AGVs in dynamic environments. The mission of an autonomous system
in an industrial setting is often to locate and pick up an object rather than safely avoiding it. LIDAR’s strong object detection and classification accuracy provides the precision necessary to complete these common tasks. Operating in the terahertz frequency
by Andreas Parr, senior marketing engineer business development, Bob Scannell, product marketing manager, and Sarven Ipek, marketing manager
F
rom the invention of the cotton gin and the steam engine during the first
industrial revolution to the development of the assembly line during the second revolution, the world has taken great leaps forward thanks to the rapid adoption of new technology. Many analysts agree — the next
industrial revolution is already upon us, driven by growth in Industry 4.0 and autonomous systems. The push to more efficient use of materials and labor in this next age of industrial discovery requires that the underlying technology continue to evolve at a rapid pace. Automated and autonomously acting
robots, vehicles, and drones, which are tightly integrated into manufacturing, mining, farming, and logistics processes, are critical pillars of the ongoing industrial revolution. To achieve the required levels of system
performance expected from autonomous applications, equipment needs to both perceive and navigate its environment. It can accomplish these goals with the help of sensing modalities whose outputs are fused and interpreted by traditional, AI, or machine learning-based algorithms. Reliability and availability are the biggest associated challenges requiring the implementation of multiple sensor
18 JUNE 2020 | IRISH MANUFACTURING
technologies in parallel, with the end goal of improving safety, efficiency, cost, and flexibility. Autonomous systems rely heavily on
high fidelity data collected by fused sensing modalities to inform AI and algorithms. Among the most commonly accepted sensors in the industry are radar, LIDAR, vision, ultrasound, and inertial sensors.
PERCEPTION SENSING: GIVING MACHINES SIGHT The challenges of Industry 4.0 are diverse. Limited space and autonomously acting machinery (robots, cobots, etc.) paired in hostile environments require radar technology that’s smaller in size, more accurate, and capable of measuring nearby targets. Imaging and classification of surrounding areas is essential to efficiency, productivity, and safety. Driven by the latest advances in RF
transceiver IC technology, radar is quickly becoming one of the important sensor technologies for perception applications. One example is 77 GHz fully integrated all-digital transceiver MMICs. High speed and linearity FMCW chirps combined with high output power, low noise transmit and receive channels, and MIMO antenna arrays now enable high performance,
range, LIDAR systems achieve fine angular resolution that translates into high resolution depth maps. With these high-res depth maps, a LIDAR system can classify objects to fuse with vision, IMU, and radar information to make reliable, mission-critical decisions. LIDAR systems are designed to work in dynamic environments, such as outdoors in bright sunlight. By using narrow pulses of 9xx nm and 15xx nm wavelengths, and driving them with high power, LIDAR is able to see farther in these challenging conditions. In addition, the narrow pulses allow for finer depth resolution to detect multiple targets within a pixel, while the infrared light at 9xx and 15xx has less solar radiation. Numerous challenges must be
overcome to encourage the mass adoption of LIDAR systems. These include complex and costly signal chains, optical design issues, and system test and calibration. Developments are currently underway to integrate these signal chains and reduce their complexity, size, power requirements, and overall cost of ownership.
NAVIGATION SENSING: GIVING MACHINES FEELING As sensors proliferate on industrial machines, and the data available from them becomes richer, the significance of their location and relative motion increases as well. Autonomy often relates to mobility, and thus pinpointing a vehicle’s position, guiding a machine’s movement, and precisely steering their instruments are key enablers. Detecting such motion with precision allows more difficult and valuable application usage, where safety and reliability are
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