Category Archives: Robotics

Robots with Eyes and Brain

In the manufacturing industry, a huge transformation is taking place—machine vision—and it is growing at astronomical proportions. This includes all types of machine vision. For instance, the market is expecting 3D machine vision to double in size during the coming six years. As of now, this technology is proving to be a vital component in many modern solutions for automation.

Several factors contribute to the increasing adoption of this technology in manufacturing. While there is greater demand for automation solutions as the industry grapples with labor shortages, the cost of automation has decreased tremendously—sensors, cameras, robotics, and processing power are now substantially cheaper—enabling greater deployment.

Technological performance has also jumped up a notch higher, and machine vision systems now have the ability to process substantial amounts of information within a fraction of a second. Finally, machine learning algorithms and advanced artificial intelligence are transforming the data collected by machine vision even more versatile, allowing manufacturers to better realize the power from those solutions. Incorporated into automation solutions, machine vision is now producing better outcomes.

The vision system of a machine is basically made up of a number of disparate parts. These include the camera, lenses, sources of lighting, robotic movements, processing computers, application-specific software, and artificial intelligence algorithms.

While the camera forms the eyes of the system, machine vision can have several types of cameras depending on the application’s needs. An automated solution may have various cameras with different configurations.

For instance, there can be static cameras, for placing in fixed positions. These usually have a more bird’s eye view of the process, useful in applications where speed is imperative. On the other hand, dynamic cameras placed on the end of robotic arms can come much closer to the process, resulting in much higher accuracy and detailed capture.

Another important aspect of the vision system is its computing power. This is the brain of the system that helps the eyes (cameras) to do their work. Computation resources, coupled with machine learning algorithms, must not be confused with traditional machine vision applications. Companies offering machine vision capability also offer software libraries for implementation.

While manufacturers design their systems specifically for application users, others offer them targeted toward software programmers. Ultimately, the software provides the machine vision system with advanced capabilities offering a dramatic impact for manufacturers. Programs are available for control of tasks along with the ability to provide feedback from the line with valuable insights.

Machine vision-guided systems are gaining steam as a concept for replacing basic human capabilities. For instance, machine vision for assembly lines enables an increasing range of processes and applications.

Typical applications of machine vision include assembly processes for power tools, medical equipment, home appliances, and industrial assembly lines. Most assembly steps in the fabrication of electronic equipment can benefit from the use of machine vision, as it offers a substantial increase in the level of precision achieved.

For instance, machine vision improves inspection of component placement of tiny surface mount components on printed circuit boards before they go for soldering. It improves the line throughput, while not succumbing to fatigue as a human inspector would.

Cooling Machine Vision with Peltier Solutions

The industry is using machine vision for replacing manual examination, assessment, and human decision-making. For this, they are using video hardware supplemented with software systems. The technology is highly effective for inspection, quality control, wire bonding, robotics, and down-the-hole applications. Machine vision systems obtain their information by analyzing the images of specific processes or activities.

Apart from inspection systems, the industry also uses machine vision for the sophisticated detection of objects and for recognizing them. Machine vision is irreplaceable in collision avoidance systems that the next generation of autonomous vehicles, robotics, and drones are using. Recently, scientists are using machine vision in many machine learning and artificial intelligence systems, such as facial recognition.

However, for all the above to be successful, the first requirement is the machine vision must be capable of capturing images of high quality. For this, machine vision systems employ image sensors and cameras that are temperature sensitive. They require active cooling for delivering optimal image resolutions that are independent of the operating environment.

Typically, machine vision applications make use of two types of sensors—CCD or charge-coupled devices, and CMOS or complementary metal-oxide semiconductor sensors. For both, the basic functionality is to convert photons to electrons that are necessary for digital processing. Both types of sensors are sensitive to temperature, as thermal noise affects their image resolution, and thermal noise increases with the rising temperature of the sensor assembly. This depends on environmental conditions or the heat generated by the surrounding electronics, which can raise the temperature of the sensor beyond its maximum operating specification.

By rough estimation, the dark current of a sensor doubles for every 6 °C rise in temperature. By dropping the temperature by 20 °C, it is possible to reduce the noise floor by 10 dB, effectively improving the dynamic range by the same figure. When operating outdoors, the effect is more pronounced, as the temperature can easily exceed 40 °C. Solid-state Peltier coolers can prevent image quality deterioration, by reducing and maintaining the temperature of the sensor to below its maximum operating temperature, thereby helping to obtain high image resolution.

However, it is a challenge to spot cool CCD and CMOS sensors in machine vision system applications. Adding a Peltier cooling device increases the size, cost, and weight. It also adds to the complexity of the imaging system. Cooling of imaging sensors can lead to condensation on surfaces exposed to temperatures below the dew point. That is why vision systems are mainly contained within a vacuum environment that has insulated surfaces on the exterior. This prevents the build-up of condensation over time.

The temperature in the 50-60 °C range primarily affects the image quality of CCD and CMOS sensors. However, this depends on the quality of the sensor as well. For sensors in indoor applications just above ambient, a free convection heat sink with good airflow may be adequate to cool a CMOS sensor. However, this passive thermal solution may not suffice for outdoor applications. Active cooling with a Peltier cooling solution is the only option here.

Astronomical Growth of Machine Vision

Industries are witnessing rapid growth of machine vision. This technology being a vital component of the industry’s modern automation solutions, they expect the market for 3-D machine vision to nearly double in the next six years. In the manufacturing context, two major factors contribute to this increase in adoption of the machine vision technology. The first is due to the industry facing acute labor shortage problems, and the second is the dramatic decrease in hardware costs.

Additionally, with an increase in technological performance, the industry needs machine vision systems to process ever-expanding amounts of information every second. Moreover, with the advent of machine learning and advanced artificial intelligence algorithms, data collected from machine vision systems are becoming more valuable. The industry is rightly realizing the power of machine vision.

So, what exactly is machine vision? What makes a robot see? A vision system typically is a conglomeration of many parts that include the camera, lighting sources, lenses, robotic components, a computer for processing, and application-specific software.

The camera forms the eye of the system. There are many types of cameras that the industry uses for machine vision. Each type of camera is specific for a particular application need. Also, an automation solution may have many cameras with different configurations.

For instance, a static camera typically remains in a fixed position in a scenario where speed is imperative. It might have a bird’s eye view of the scene below it. On the other hand, a robotic arm may mount a dynamic camera at its end, to take a closer look at a process, thereby picking out higher details.

One of the important aspects of the vision system is its computing power. In fact, this is the brain to help the eye understand what it is seeing. Traditional machine vision systems were rather limited in their computing powers. Modern machine vision systems that take advantage of machine learning algorithms require far greater computation resources. They also depend on software libraries for augmenting their computing capabilities.

Machine vision manufacturers design these capabilities specifically for application users. They design the software to provide advanced capabilities for machine vision systems. These advanced capabilities allow users to control the tasks for the machine vision, such that they can gain valuable insights from the visual feedback.

With the industry increasingly using vision for assembly lines, the concept of a vision-guided system replacing basic human capabilities is on the upswing in a wide range of processes and applications.

One of the major applications of machine vision is inspection. As components enter the assembly line, machine vision cameras give them a thorough inspection. They look for cracks, bends, shifts, misalignment, and similar defects, which, even if minor, may lead to a quality issue later. The machine vision compares the crack, and if larger than a specified size, rejects the component automatically.

In addition to mechanical defects, machine vision is capable of detecting color variations. For instance, a color camera can detect discoloration and thereby reject faulty units.

The camera can also read product labels, serial numbers, or barcodes. This allows the identification of specific units that need tracking.

Tiny Batteries Drive Microbots

Microbots are mobile robots, with characteristic dimensions below one micrometer. They are a part of the bigger family of common larger robots and a growing number of smaller nanorobots. In fact, the nature of microbots is common to both their larger and smaller cousins. Being autonomous, microbots use their onboard computers to move in insect-like maneuvers. Often, they are a part of a group of identical units that perform as a swarm does, under the control of a central computer.

With their insect-like form being a common feature, microbots are typically cheap to develop and manufacture. Scientists employ microbots for swarm robotics, using many of them and coordinating their behavior to perform a specific task. Combining many microbots compensates for their lack of individual computational capability, producing a behavior resembling that of an anthill or a beehive where insects cooperate to achieve a specific purpose.

With the field of microbotics still growing, microbots have a long way to develop further. Researchers are working with these devices, and they are investing their money, time, and effort in improving their capabilities.

With each new iteration, scientists are empowering microbots with more processing power, newer modes of locomotion, a larger number of sensors, and expanding their storage methods while providing them with newer techniques of energy harvesting. Recently, there has been a big breakthrough in tiny batteries that can help microbots drive further than ever before.

Generating a 9 VDC output, these tiny batteries are capable of driving motors directly. They stack multiple layers while turning components into packaging.

Several universities and a battery corporation have joined hands in creating the tiny batteries, a novel design that not only produces a high voltage but also boosts its storage capacity.

To unlock the full potential of microscale devices such as microbots, batteries must not only be tiny, they must also be powerful. According to the team that developed the tiny battery, its innovative design uses an improved architecture for its electrodes.

However, this was an unprecedented challenge. As the battery size reduces, the packaging begins to take up more of the available space, leaving precious little for the electrodes and the active ingredients that give the battery its performance.

Therefore, in place of working on the battery chemistry, the team started to work on a new packaging technology. They turned the negative and positive terminals of the battery into actual packaging, thereby saving considerable amounts of space.

By growing fully-dense non-polymer electrodes and combining them with vertical stacking, the team was able to make micro batteries that do not require carbon additives for electrodes. This allowed the micro batteries to easily outperform competitive models in capacity and voltage.

According to the team, limitations of power-dense micro- and nano-scale battery design were primarily due to cell design and electrode architecture. They have successfully created a microscale source of energy that has both volumetric energy density and high power density.

The higher voltage helps to reduce the electronic payload of a microbot. The 9 VDC from the tiny battery can power motors directly, bypassing energy losses associated with voltage boosting, allowing the small robots to either travel further or send more information to their human operators.

A Wheel-to-Leg Transformable Robot

With the general audience preferring to engage in the search for anthropomorphization, the popularity of biped and quadruped robots has been growing. At the Worcester Polytechnic Institute, researchers have innovated a robotic system that they call the OmniWheg—a robotic system that adapts its configuration based on the surrounding environment that it is navigating. They introduced this robot in a paper in the IEEE IROS 2022, and pre-published it on arVix. OmniWheg has its origins in an updated version of whegs, which was a mechanism with a design to transform the wings or wheels of a robot into legs.

Although the researchers would have liked to make the robot capable of going everywhere they go, they found the cost of legs to be very high. While evolution has provided humans and animals with legs, the researchers found that a robot with legs would be highly energy inefficient. While legs could make the robot more human or animal-like, they would not be able to complete tasks quickly and efficiently. Therefore, rather than develop a robot with a single mechanism for locomotion, the team proceeded to create a system that switched between various mechanisms.

The team found that about 95% of the environments at homes and workplaces are flat, while the rest are uneven terrains that require transitioning. Therefore, they went on to develop a robot that performs with a high-efficiency wheel-like arrangement for 95% of the cases, specifically transforming to the lower-efficiency mechanism for the remaining 5%.

The researchers, therefore, created a wheel that changed its configuration for climbing stairs or for circumventing small obstacles. For this, they utilized the concept of whegs,  wing-legs, or wheel-legs, which is popular in the field of robotics.

In the past few years, the team developed and tested several wheel-leg systems. However, most of them were not successful, as the left and right sides of the wheel-leg system would not coordinate well or align properly when the robot tried climbing stairs.

Finally, the team could solve the coordination issues by using an omnidirectional wheel. This enabled the robot to align on-the-fly, but without rotating its body. Therefore, the robot can move forward, backward, and sideways at high efficiency, and remain in a stable position without expending any energy. At the same time, the robot can also climb stairs swiftly, when necessary.

For correct operation, the wheg system that the team developed requires a servo motor to be added to each wheel and operated with a simple algorithm. As the design is straightforward and basic, any other team can easily replicate it.

According to the researchers, the system has abundant advantages with very few drawbacks. The team feels it can pose a threat to the legged robots, and any robotic application can adopt this design.

The team has evaluated their OmniWheg robot system on a multitude of real-world indoor scenarios. This includes climbing steps of various heights, circumventing obstacles, and moving/turning omnidirectionally. They found the results to be highly promising, and the wheel-leg robot could successfully navigate the common obstacles quite flexibly and efficiently.

Magnetic Position Sensing in Robots

Robots often operate both autonomously and alongside humans. They greatly benefit the industrial and manufacturing sectors with their accuracy, efficiency, and convenience. By monitoring motor positions at all times, it is possible to maintain not only system control but also prevent unintentional motion, as this can cause system damage or bodily harm.

Such monitoring of motor positioning is possible to implement by contactless angle encoding. It requires a magnet mounted on the motor shaft and provides an input for a magnetic encoder. As dirt and grime do not influence the magnetic field, integrating such an arrangement onto the motor provides a compact solution. As the encoder tracking the rotating magnet provides sinusoidal and 90-degree out-of-phase components, their relationships offer quick calculations of the angular position.

As the magnet rotates on the motor shaft, many magnetic encoding technologies can offer the same end effect. For instance, Hall-effect and magnetoresistance sensors can detect the changing magnetic field. 3D linear Hall effect sensors can help with calculating angular positions, while at the same time, also offering compensations for temperature drift, device sensitivity, offset, and unbalanced input magnitudes.

Apart from signal-chain errors, the rotation of the magnet also depends on mechanical tolerances. This also determines the quality of detection of the magnetic field. A final calibration process is necessary to achieve optimal performance, which means either harmonic approximation or multipoint linearization. With calibration against mechanical error sources, it is possible for magnetic encoding to achieve high accuracy.

The driving motor may connect directly to the load, through a gearbox for increasing the applied torque, through a rack and pinion, or use a belt and screw drive for transferring energy elsewhere. As the motor shaft spins, it transfers the kinetic energy to change the mechanical position somewhere in the system. In each case, the angle of the motor shaft correlates directly to the position of the moving parts of the system. When the turns ratio is different from one, it is also necessary to track the motor rotations.

Sensorless motor controls and stepper motors do not offer feedback for the absolute position. Rather, they offer an estimate of the position on the basis of the relative change from the starting position. When there is a loss of power, it is necessary to determine the actual motor position through alternate means.

Although it is possible to obtain the highest positional accuracy through the use of optical encoders, these often require bulky enclosures for protecting the aperture and sensor from contaminants like dirt and dust. Also, it is necessary to couple the mechanical elements to the motor shaft. If the rotational speed exceeds the mechanical rating of the encoder, it can lead to irreparable damage.

No mechanical coupling is necessary in the case of magnetically sensed technologies like magnetoresistive and Hall-effect sensors, as they use a magnet mounted on the motor shaft. The permanent magnet has a magnetic field that permeates the surrounding area, allowing a wide range of freedom for placing the sensor.

New Requirements for Miniature Motors

Innovations in the field of robotics are resulting in the emergence of smarter and smaller robotic designs. Sensor technologies and vision systems use robotic applications in warehousing, medical, process automation, and security fields. Disruptive technologies are creating newer opportunities for solving unique challenges with miniature motors. These include the robotic market for efficient and safe navigation through warehouses, predictable control of surgical tools, and the necessary endurance for completing lengthy security missions.

With industries transitioning to applications requiring collaborative robotics, they need systems that are more compact, dexterous, and mobile. Tasks that earlier required handling by human hands are driving the need for miniaturized motors for mimicking both the capability and size of the hands that accomplished the work.

For instance, multiple jointed solutions representing the torso, elbow, arm, wrist, etc. require small, power-dense motors for reducing the overall weight and size. Such compact solutions not only improve usability but also improves autonomy and safety, resulting in faster reaction times due to lower inertia. Therefore, robotic grippers, exoskeleton, prosthetic arms, and humanoid robots require small, high-power density motors. Power density is the amount of power a motor generates per unit of its volume. A motor that generates greater amounts of power in a small package, has a higher power density. This is an important factor when there is a space constraint, or where a high level of output is necessary when a limited space.

Manufacturers can miniaturize motors with high power densities. Alternately, they can increase the capability of current designs. Both options are critical in reducing the space that motion elements occupy. High efficiency is necessary to obtain the maximum power possible from a given design. Here, BLDC or brushless DC motors and slot-less motor designs in combination with efficient planetary gearboxes can offer powerful solutions in small packages. Brushless solutions are flexible enough for engineering them to meet customer requirements like long and skinny designs, or short, flat, low-profile configurations.

Smooth operation and dynamic response can result in these miniature motors being dexterous and agile. Slot-less BLDC motors achieve this by eliminating detent torque, thereby providing precise dynamic motion with their lower inertia. Applications requiring high dynamics, such as pick-and-place systems and delta robots, must be able to accelerate/decelerate quickly and constantly. Coreless DC motors and stepper motors with disc magnets are suitable for applications requiring critical characteristics like high acceleration as they have very low inertia.

Ironless brushed DC motors with their high efficiency, are the best choice for battery-powered mobile applications to extend their operational life between charges. Several robotic applications now run on battery power, thereby requiring motors with high efficiency for longer running times. Other applications require high torque at low speeds, and it is possible to achieve this by matching the motor with a high-efficiency gearbox.

Some applications that are inhospitable to humans may need robot systems capable of enduring difficult environmental conditions. This may include tremendous vibration and shock. With proper motor construction, it is possible to improve their reliability and durability when operating under such conditions.

Encoders for Autonomous Mobile Robots

Whether it is AMR or autonomous mobile robots, AGC or automated guided carts, AGV or automated guided vehicles, various types of robots or robotics are increasingly important to the industry. They use these robots to move parts and materials from one place to another in every environment. For instance, goods move from manufacturing to warehouse, and thence to grocery stores to face customers.

It is important that these automated machines work correctly because precision is a vital requirement. This requires reliable motion feedback to the controllers. This is where encoders come in. For instance, autonomous motion applications requiring motion feedback are useful in steering assembly, drive motors, lift controls, and more.

The industry uses several automated carts and vehicles. They use them for lifting products and materials onto and from shelves and floors in warehouses and other storage areas. To do that reliably and repeatedly, these machines require accurate and precise motion feedback. This ensures that materials and products reach where they need to go, without incurring damages.

The Encoder Product Company offers to draw wire solutions, and encoders with rack-and-pinion gears provide reliable motion feedback. This ensures all lifts stop at the right locations, thereby moving materials and products safely to their destinations. Their motion feedback options for lift control involve Model LCX, for high performance with absolute feedback option, and Model TR2, a rack-and-pinion gear as an all-in-one unit.

The Model LCX135 is one of a draw wire series, providing an excellent solution for the control of lifts. Internally, incremental and absolute encoders provide excellent lift control feedback using the CANopen communication protocol.

Automated carts and vehicles require drive motor feedback. As they move around facilities like warehouses, the controller in these vehicles needs reliable motion feedback to ensure the motors are in the proper transit areas/corridors designated for them. The motion feedback also ensures they stop and start accurately.

Motion feedback devices from the Encoder Product Company provide this reliable, repeatable motion feedback. Their Model 15T/H is a compact and high-performance encoder. It is available in the blind-hollow bore or thru-bore designs. The Model 260 is a more economical and compact encoder with a large thru-bore design. The next model 25T/H is a high-performance 2.5” encoder. While Models 25T and 260 are incremental encoders, absolute encoders are also available, and they use the same CANopen communication protocol.

To ensure the correct drive path ad steering angle, the steering assembly also needs to provide precision feedback. Absolute encoders provide the best way to ensure proper motion feedback for these steering assemblies. This is because with absolute encoders it is possible to ensure smart positioning while providing the exact location while in a 360-degree rotation.

The Encoder Product Company offers several absolute encoders. Among them is the Model A36HB, a compact absolute encoder with a 36 mm blind hollow bore. Another is the Model A58HB, an absolute encoder with a 58 mm blind hollow bore.

Where safety is considered paramount, the Encoder Product Company offers redundant encoders. These are simple solutions and economical also. Using redundant encoders allows the application to rely on different technologies, ensuring at least one encoder will continue to function even when the other has failed.

Handling Grippers

Material handling in industries is increasingly relying on grippers. Industries, ranging from automotive assembly to electronics manufacturing, all handle their materials with grippers. The increasing requirement for grippers is evident from the market being worth $100 million in North America alone today, with the number expectedly growing by 5% annually.

The sudden spurt in growth in the use of grippers can be attributed to the rise in robotics. This includes industrial robots taking on special tasks like handling increasingly complex workpieces. Designers now can take their pick from more types of grippers than before. However, even with the latest developments in robotics and gripper technology, picking the most suitable gripper for a specific application can be a daunting task.

The market today has a plethora of grippers including mechanical, adaptive, soft, magnetic, and vacuum types, with each type offering key design features and benefits. For instance, adaptive and soft grippers adapt themselves to the contours of the workpiece and are useful in various handling applications.

Mechanical grippers, both electric and pneumatic types, are popular for handling applications. Of these, the pneumatic types make up about 90% of the demand, as these tend to be lighter and more cost-effective compared to the electrical types. Being more suitable for harsh environments, pneumatic grippers have faster cycle rates and higher grip forces.

On the other hand, electric grippers offer their users better travel and force control along with greater precision. However, the presence of motors and other internal components in these grippers tends to make them heavier and increases their upfront costs.

Irrespective of being pneumatically or electrically operated, there are several design classes of mechanical grippers. For instance, parallel grippers have fingers that can pull directly apart. The most common among these is the two-finger parallel gripper. These make up more than 85% of the market for mechanical grippers. Another version is the three-finger gripper, and it can perform centering functions and handle round objects.

Other classes of mechanical grippers include the angular and radial versions. These typically have fingers that open at an angle. For instance, angular grippers open their fingers only to 30-degrees, while radial grippers can open their fingers up to 180-degrees, allowing them to handle workpieces of varying dimensions while being slower than angular grippers.

Selecting grippers for a specific application requires considering important factors. Depending on the nature of the workpiece, the designer must consider the gripping force required, the guiding strength of the jaw, and the type of the gripper itself. For instance, long gripper fingers require a long lever arm to exert greater torque on the jaws. There are flat finger designs that offer a friction-based grip for durable and bulky parts. On the other hand, handling slippery parts that require precision placement must use encapsulated designs.

Encapsulated designs have fingers with a profile shape matching the object they will handle. Usually, the fingers will be curved to hold a round object. This helps to retain the object in a specific position while preventing that part from dropping if the pressure is lost.

What is Ambient Sensing?

Although smart homes have been around for several years now, this industry is rather nascent. Even though we are familiar with the use of Amazon Alexas and Google Homes as smart devices, but for smart homes, they have their limitations.

Smart devices do use technologies promising levels of interoperability and convenience that were unheard of a few years ago. However, they have not been able to fulfill current expectations. For instance, they struggle if there is no home network, cannot use unprocessed data, and are typically standalone devices.

Movies provide a better concept of a smart home. They present a futuristic building with levels of autonomy and comfort far beyond what the current technology can provide. In the real world, our ability to interact with them is rather limited.

For instance, the smart technology available at present allows interaction with voice commands only, thereby limiting their autonomy. Although the current technology boasts of voice recognition, this is still frustrating and cumbersome to use. Most people seek a seamless experience that comes with higher intuitive or human interaction.

For instance, it is still not possible to unlock a smart home simply by improving voice commands. Although audio sensors do form a crucial element for intuitive interaction with a smart home, making them a part of a sensor array for providing better contextual information would be a better idea. For genuinely smart home, the devices must provide a more meaningful interaction, including superior personalization for contextualized decision-making.

While it may be possible for manufacturers to pack in unique sensor arrays in devices, some sensor types could prove to be more useful. For instance, cameras provide huge amounts of information, and smart systems could make use of this fact to perceive the smart home in a better way. Adding acoustic sensors, and gas sensors along with 3-D mapping could be one way of bringing smart environments to the next level.

By collating these inputs, smart devices can understand and implement individual preferences better. For instance, depending on who has entered or exited the room, a smart device can change the sounds, lights, safety features, and temperature matching that person’s profile. Smart devices must not limit themselves to comprehending the ambient alone, but be capable of changing the environment, even without direct inputs.

These features could go beyond providing comfort alone. For instance, with motion sensors, the device could extend security. Along with motion sensing, individual recognition, and 3-D mapping could make homes much safer. For saving energy, sensors for presence, daylight sensing, and temperature measurements could dim lights or adjust air conditioning for better comfort on hot days.

One of the issues holding back such implementation is consumer privacy. While homeowners have grown accustomed to smart speakers, endless examples are available of data-mining organizations that observe the consumer’s daily interaction with these devices. For instance, Amazon’s Astro robot has been accused of data harvesting and there is criticism of Facebook’s smart glasses by the Data Privacy Commission in Ireland. As devices get smarter and use more ambient technology, consumers will have to share greater amounts of data than they are doing at present.