Using an electrokinetic propulsion system (EKPS) that generates an electrical field and manipulates surrounding ions to drive fluid motion, the robotic device can move at speeds up to one body length per second.
The EKPS provides several benefits for the robotic device, including eliminating moving parts, which increases durability. The robotic device can be repeatedly handled with a micropipette, transferred from one sample to another, and survive repeated exposure to various liquids.
The electrical field generation system provides precise control of the robotic device’s motion, including direction, speed, and movement pattern. The EKPS also allows the robotic device to perform complex motions and coordinate motion among multiple robotic devices.
One of the primary advantages of the EKPS is the elimination of mechanical components; since there are no mechanical parts, the friction associated with microscale movement is eliminated. Additionally, because there are no moving parts, the robotic device’s durability increases. The robotic device can be repeatedly exposed to various liquids without suffering any damage.
In addition to eliminating moving parts, the EKPS is a “solid state” system. Unlike mechanical systems that use moving parts, the EKPS uses the application of voltage to an electrode to drive fluid movement. Therefore, the EKPS does not have any mechanical components that will fail due to wear. The EKPS is thus a well-suited method for controlling the motion of a robotic device at the microscale.
Since the EKPS eliminates the need for mechanical components, the robotic device’s motion can be controlled by electronic signals. Therefore, the EKPS can provide precise control of the robotic device’s motion, including direction, speed, and motion pattern. In addition, the EKPS can control multiple robotic devices simultaneously. Therefore, the EKPS can be used to coordinate the motion of numerous robotic devices to perform complex tasks.
The EKPS operates by manipulating ions in the surrounding fluid using an electrical field. When an electrical field is applied to an electrolyte solution, the ions are attracted to the positive or negative electrode, causing the fluid to move. This movement of the fluid creates the thrust that pushes the robotic device.
Unlike mechanical systems that rely on the rotation of wheels or propellers, the EKPS generates thrust solely by attracting ions to the electrode. Therefore, the EKPS is a very efficient method for controlling the motion of a robotic device at the microscale.
Additionally, the EKPS can be controlled electronically. Therefore, the EKPS can be easily programmed to control the robotic device’s motion. This contrasts with mechanical systems, which often require manual adjustment of mechanical components to control the robotic device’s motion.
The EKPS is also a very reliable method for controlling the motion of a robotic device. Since the EKPS relies on electronic signals to control the robotic device’s motion, it is much less likely to experience mechanical failure than mechanical systems. This reliability is necessary at the microscale, where the wear and tear of mechanical components often causes mechanical failures.
Finally, the EKPS can control multiple robotic devices simultaneously, meaning it can be used to develop multi-robot systems capable of performing complex tasks. This contrasts with mechanical systems, which are often designed to control the motion of a single robotic device.
Engineering Deep Dive: How Microscale Computing Works
Computational capability at the micro-scale is a fundamental engineering challenge. The key constraint is power – the robots have only enough power to consume about 75 nW. To achieve sufficient computation at the micro-scale, engineers were forced to take drastic steps to reduce power consumption. One method used was voltage scaling, which reduces the voltage across each component to minimise power consumption. The voltage scaling achieved by the team was impressive – the processors operated at voltages that approached the theoretical limits of silicon transistors. This resulted in over 1,000-fold reductions in power consumption when compared to traditional micro-processors.
Voltage scaling is achieved by operating the transistor in the sub-threshold region. The sub-threshold region is the range of operation below the threshold voltage at which a transistor begins to conduct. At the micro-scale, the sub-threshold region provides the optimal trade-off between leakage current and switching speed. While leakage current is undesirable, the switching speed enabled by sub-threshold operation is essential to maintaining processor performance.
The processors developed by the team utilised voltage scaling to maintain acceptable performance while consuming extremely low power. The ability to achieve such low power consumption is critical to the success of the robots developed by the University of Pennsylvania and the University of Michigan.
Another method used to reduce power consumption was to implement a highly optimised computer architecture. Traditional computers use a standard set of instructions that the processor interprets to perform everyday functions. For example, a processor may have an instruction that simply increments a register value by one. However, this type of instruction can be implemented using fewer instructions in a custom-designed processor.
In the case of the micro-robots developed by the team, the instruction set is highly customised for the tasks that the robots are intended to perform. The processors developed by the team are highly optimised for controlling the robots’ movement, resulting in a dramatic increase in computations per unit of time.
While the processors developed by the team utilise a highly customised instruction set, the architectures remain relatively traditional. They consist of a central processing unit (CPU), memory, and input/output interfaces. The CPU performs the computations, memory stores data, and input/output interfaces allow the robots to interact with the outside world.
Despite the use of a highly customised instruction set, the CPUs developed by the team still utilise traditional computer architecture concepts, such as registers, buses, and caches. Registers store temporary data during computations, buses connect components, and caches improve access to frequently used data.
While the CPUs developed by the team utilise traditional computer architecture concepts, they do so in a highly optimised manner. The processors have been designed specifically for controlling robots, and their architecture has been optimised accordingly. The result is a processor capable of performing complex computations at extremely low power.
In addition to using voltage scaling and highly optimised computer architectures, the team also made significant advancements in temperature sensing and communication. Temperature sensing is critical to the robots’ success, as they must monitor their internal temperature to prevent overheating. The team developed a highly sensitive temperature sensor that utilises the thermal-voltage variation in semiconductor junctions to determine the robots’ internal temperature.
The temperature sensor developed by the team consists of two identical transistors: one is directly connected to the processor, while the other is connected through a resistor network. By comparing the output currents of the two transistors, the robot’s internal temperature can be determined.
They also developed a highly efficient method for communicating with the robots. The robots utilise light pulses to receive instructions that contain information about the task they should perform. The light pulses are transmitted to the robots via a photodiode, which converts them into electrical signals that are then processed by the robots.
The communication system developed is highly efficient, as it utilises light pulses that encode information about the task the robot should perform. The light pulses are transmitted to the robots via a photodiode, which converts them into electrical signals for processing.
The new communication system is highly flexible, as it can be easily modified to accommodate changes in the task that the robot is intended to perform. This flexibility is a significant advantage of the communication system developed by the team, as it allows for rapid modification of the robot’s behaviour in response to changing circumstances.
The robots use photovoltaic effects in the solar panel to encode instructions and modulate the light pulses sent to them to turn them on/off. The light-pulse modulations are similar to those used in fibre-optic communication systems, but scaled down to the micro-scale. Each robot has a unique identifier embedded in its circuitry and can therefore be individually programmed, even if multiple robots are in the same environment.
The next significant step in the development of micro-scale robotics is to continue to push the boundaries of what is actually possible. There are numerous areas where further innovation is needed, including the development of more powerful microprocessors, more sophisticated communication methods, and improved methods for controlling robot motion.
As the field of micro-scale robotics continues to evolve, we can expect to see ever-more sophisticated robots capable of performing a wide range of tasks across a variety of environments.
