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SMART MANUFACTURING THE AUTONOMOUS
INDUSTRIAL REVOLUTION By Andreas Parr, senior marketing engineer business development, Bob Scannell, product marketing manager, and Sarven Ipek, marketing manager, all with Analog Devices
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 labour in this next age of industrial discovery requires that the underlying technology continue to evolve at a rapid pace.
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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 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. The table here highlights the benefits and limitations to each perception sensing modality and the need for multiple sensors in a system.
Sensing Vision LIDAR Radar Ultrasonic 28 Key Benefits Highest resolution, colour High resolution, measured range
Most weather, measured range, measured velocity
All weather, measured range, low- est cost
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 is 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 77GHz 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, 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 is 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 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
Limitations
Night-time, bad weather, estimated range
Bad weather Low resolution
Short range, low resolution, slow response
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.
Primary Contribution
3D mapping (>15m), first level classification, small obstacle detection
3D mapping (>15m), first level classification, small obstacle detection
Object detection and tracking Low speed, short range detection Autumn 2023 UKManufacturing
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