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The use of robotic technologies to improve the rate of manufacturing various types of electronic devices and semiconductors has a lengthy history that continues to grow with the technological advancements of the robotics industry. More specifically, the ability of Delta robots, in particular, to work at a high speed while maintaining the highest level of precision and cleanliness, is a critical component of semiconductor manufacturing1.
Further development in both of these technologies has proposed the potential integration of semiconductor devices into robots. Although this novel generation of robotics remain in the early stages of development, researchers are hopeful that these revolutionary robotic systems will exhibit exceptional properties for a wide range of industrial applications.
Semiconductors in Flying Insect Robots
The advancements in the field of small Unmanned Aerial Vehicles (sUAVs) has allowed robotic devices to decrease in size without compromising their ability to conduct sophisticated odometry tasks, such as their autonomous regulation of flight speed and path integration, while also smoothly landing on unfamiliar targets and optimizing their routes around a set of specified targets.
To perform these tasks, a variety of visual inputs, sensory processing components are integrated into the sUAVs, particularly robotic insects, in an effort to replicate the behaviors and cognitive processes of insects to perform various different tasks.
Of the various different types of visual systems utilized in robotic applications include the lightweight First-Person View (FPV) sensors that can be made available at a low cost to industries. More specifically, two commonly used FPV cameras used in small robotics include charged coupling device (CCD) and complementary metal oxide semiconductors (CMOS)2.
For visual purposes in insect robots, it is currently more common to find CCDs due to their unique ability to perform particularly well under varying light conditions, while also remaining less susceptible to rolling shutter artifacts.
CMOS for Robot Motion Control
Robots are often credited with the ability to perform repetitive and potentially dangerous tasks that humans would otherwise be unable to do. Additionally, the ability of robots to resist damage in harsh environmental conditions, such as outer space or at the bottom of the ocean, or fit in hard to reach places, support the continued interest scientists have in developing novel robotic devices.
To perform their daily tasks, robots have been traditionally powered by computer and electronic programming that only functioning in well-controlled environments.
Furthermore, current robots are often equipped with implantable batteries or power grids that often limit their working life span. As various industries, such as those within the military and scientific sects, are becoming increasingly interested in using autonomous micro-robots, there is an urgent need to improve the technology of robotic motion control units.
To address these concerns, researchers have utilized CMOS technology in a wide variety of unique ways. For example, a 2014 study conducted at Northeastern University in Boston, Massachusetts developed an excitatory CMOS neuron oscillator circuit design that is composed of both CMOS neurons and CMOS excitatory synapses.
In their design, the researchers connected both the CMOS neurons and CMOS excitatory synapses to a close loop, during which the synapse supplies the current to the postsynaptic electronic neuron in a similar manner to which biological synapses occur3.
Simulation of this system, which operated at a 1.8 V power supply, found that the CMOS technology successfully reduced the overall power consumption and size of the circuit. The researchers of this study are hopeful that their design can be applied in future bio-mimetic micro-robotic devices.
References
- “What’s New with Robots in Electronics and Semiconductors?” – Robotics
- Sabo, C., Chisholm, R., Petterson, A., & Cope, A. (2017). A lightweight, inexpensive robotic system for insect vision. Arthropod Structure & Development 46(5), 689-702. DOI: 10.1016/j.asd.2017.08.001.
- Lu, J., Yang, J., Kim, Y., Ayers, J., & Kim, K. (2014). Implementation of Excitatory CMOS Neuron Oscillator for Robot Motion Control Unit. Journal of Semiconductor Technology and Science 14(4), 383-390. DOI: 10.5573/JSTS.2014.14.4.383.
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