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Electrical Circuit

An electrical circuit is a loop which provides a path for electric current (electric charge) to flow. This loop must be closed. In other words, the current must be able to flow from positive to negative terminals otherwise the flow will not take place. The charge is made possible by a source such as a battery which motivates the electrons to move in the conductor. So it is the movement, in other words the flow of these electrons that constitutes the electrical charge. Note that this happens from negative to positive terminal which is the opposite of accepted convention for current direction. In this closed loop we mentioned above, there are components we want, to make our electronic devices possible, such as motors, resistors, inductors capacitors, light bulbs, logic gates and so on.

The loop must be made of conductors. This conductor is most commonly conductive metal wire but other mediums such as conductive polymers or liquids, are also possible. Current can also be carried by electromagnetic induction, which requires no physical medium. Examples include transformers, radio frequency signals.

Conductors, Insulators, Semiconductors


Conductors are the materials that easily allow flow of electric current upon application of voltage, such as copper.

Conductivity is the measure of how easily current will flow through that material and shown by the symbol σ (sigma). Its unit is Siemens / meter (S/m) but usually milliSiemens / meter is used. It is a characteristic property a material. In other words, it is not affected by the geometry or size of material.


Insulators are the materials that do not allow or very hardly allow the flow of electrical current upon application of voltage. Example: Glass.

Resistivity is the exact opposite of conductivity and shown by the symbol ρ (rho). So if we were to write resistivity in terms of conductivity:

ρ = 1/ σ

And its unit is:

Ohm meter (Ω.m)

Like conductivity, resistivity is also a characteristic property of the material.

Do not confuse resistivity with resistance. Unlike resistivity, resistance is not a characteristic property and depends on geometry of the material. We can find the resistance of a material if we know its resistivity and geometry. So two cables of the same material with different geometries will have different resistance. We calculate resistance from resistivity as below:



R: resistance

L: length

A: Area

So this means that as the length of a material increases, the flow of current through it will be more difficult and the resistance will increase. And when its area increases, the resistance will decrease as the current will flow easier.


Semiconductors are the materials that allow flow of current easier than resistors but harder than conductors. Examples: Silicon, Germanium.

In semiconductors, electrons can change their place (thus make current flow possible) only after a certain amount of voltage is applied. By controlling this, we can control when a current will flow or not, depending on our purpose in an electrical circuit. This key principle enables all electrical devices that we use today to function as we want.

Sensors and Transducers

Sensors and transducers can sometimes be confused because they both react to some change in their environment but they are not the same thing.


A sensor is a component in an electronic system that can detect (sense) various types of changes in the physical environment and as a result, communicate these to the bigger system it is a part of. In other words they do the same job as what our 5 senses do for us. A sensor can measure how much the change occurs and transmits this information in a convenient format  such as electrical signals to the system. The change can be about any physical quality that can be detected and measured, such as light, sound, pressure, acceleration, distance, motion, temperature, humidity and many more.

Most sensors can also be categorized as transducers. So a sensor is a specific type of transducer.


A transducer on the other hand, is a device that converts one form of energy into another. So, while the duty of a sensor is to detect, the duty of a transducer is to transform or convert. Transducers contain sensors. So a transducer is a more general term than a sensor.

Transducers can be separated into two as input and output transducers.

An input transducer takes energy in it and converts it into something such as signals that can be understood.

An output transducer converts signals into energy. For example a motor transforms electrical energy into mechanical energy.

Analog vs. Digital Electronics

We can look at electronics in two different ways, both of which have different uses, which are analog vs. digital electronics. In short, analog electronics deals with continuous, smoothly varying signals, and digital electronics is about handling discrete signals (which are either on or off or in other words, 1 or 0).


In general sense, analog means something that is comparable to / similar to something else that can continuously vary. This varying thing can be anything such as temperature, pressure, position, voltage…

So in analog electronics, the signals can be represented by varying voltage or current levels proportional to the signal.

The physical quantity is converted to analog signals by a transducer.

Analog electronics has many uses, of which we list only a few below:

It is used for signal amplification, modulation and filtering for purposes such as handling sound and audio communication. Analog systems can be used for radio communication.

Because analog signals are continuous, they can be used to precisely measure and monitor physical quantities by using sensors and transducers.

Voltage regulation and stabilization

Amplifiers, oscillators


Because analog signals are continuously, gradually varying, they can represent a lot of different values with high accuracy and resolution, with a very wide range of values.


Much more susceptible to noise and interference than digital systems, which decrease signal quality. Noise susceptibility causes data degradation or even loss, decreases data capacity of analog systems. In long distances this is pronounced even more by introduction of more noise and signals losing energy. Analog filters can be used to reduce noise and signal shaping.

During design it is more difficult to achieve noise reduction and precision.


Digital electronics deals with digital signals that either take the values on or off. We say digital because the values of on and off are represented by 1 and 0, the digits of binary numbers.

Digital circuits work with logic functions by using AND, OR, NOT logic gates and a few more. From the use of these logic gates, integrated circuits and a whole generation of our electronics devices, anything from digital watches upto supercomputers came into existence.


Digital signals are far more resistant to noise than analog signals because even if there is some noise interference, we can still easily know whether the signal is on or off ( 1 or 0). Distinguishing between different signal levels is easy.

This (1 or 0) is all that matters for us to be able to process that information, unlike analog electronics where the noise can distort the quality of signal which has a wide range of continuously varying values, some of which may be subject to degradation, get lost or change.

Noise resistance, which is the most fundamental advantage of digital electronics and dealing with discrete (1or 0) values have important positive effects:

-Making precise circuits that produce dependable signals and mass producing them is much more easier.

-Dependable, high quality signal transmission over long distances are far more easier. Even in noisy environments, digital signals can be reproduced to its original very easily.

-Data storage is easier.

-Complex operations and a wider range of tasks can more efficiently be handled with digital systems than analog.


Digital circuits require encoders and decoders, microprocessors, memory components, logic gates, flip flops, intricate coding and algorithms. This can increase costs, complexity and power consumption and make troubleshooting harder.

Digitals signals are not ideal in certain situations where analog signals fit better.

Where high resolution, continuous variations and fine details are needed, analog usually fits better due to its ability to continuously represent values. Analog systems can handle an infinite range of input values. With discrete digital values this is inherently more difficult and some information (quantity and quality) of signal may be lost which can happen during conversion of analog to digital. Some extreme values may not also be represented with digital.

When converting analog to digital signals there can also be delays . Analog systems however do not experience this, as they can represent continuously varying quantities easily. Delay is more pronounced especially during real time applications.

Digital technology progresses at a faster speed therefore obsolescence is more common.

Although the design can be simpler in some situations, making changes to digital design is more difficult. Analog systems are more flexible regarding making changes.

Robot Actuation Systems

Actuation in robotics means the systems that enable physical movement. The most common ways of actuation are by electric motors, pneumatic and hydraulic systems, which we will introduce below. But note that there are other actuation systems as well, achieved by shape memory alloys, piezoelectric action, electromagnetism, movement achieved through thermal properties of materials and more. Now let’s take a closer look at Electric motor, Pneumatic and Hydraulic actuation. 

Electric Motor Actuation: 

This is the most common way, where, movement is achieved by electric motors, which can run on AC or DC power. 

Electric motors offer a high degree of precision and motion control and may be used for almost any type or size of robotic applications.

Pneumatic Actuation: 

Pneumatic systems make use of the powerful action obtained from compressed air, that moves pneumatic cylinders (pistons). It is commonly used for robotic arms and industrial robots including especially assembly lines, where strong and swift movements are essential. Note that this comes at the expense of relatively lower precision, in comparison to electrical actuation by motors. 

The air can either be generated by a compressor exactly when needed, or be stored in a compressed air tank. Air flow is controlled by valves. 

The back and forth movement of a piston in two directions is achieved by different means, which depends on the particular application and operating environment: 

-In a single acting cylinder, the pressure is supplied only from one side and the reverse movement may be achieved by a spring, gravity, or the pressure difference between the compressed / depressurized air and the air pressure from the external environment. So in a single acting cylinder there must be an external force to achieve the movement in reverse direction. 

-The compressed air can also be introduced from both directions as necessary. This is called a double acting cylinder. Of course when introducing air from one side, it must be released from other side which must be coordinated. Double control of the cylinder from both sides means better control of the overall movements. 

The control system manages this two way movement by controlling the valves and compressors in proper timing and sequencing. 

Hydraulic Actuation: 

These systems use pressured liquids, usually oil, which can provide the strongest movements. Remember that construction equipment use this type of actuation. 

Due to the incompressible nature of liquids, strength can be achieved in a small volume (even by a small amount of movement), and also precise movements are easy to obtain. 

Therefore hydraulic systems are used where we need both strength and precise control. 

If we want to compare Pneumatic vs. Hydraulic systems: 

Hydraulic systems are  

generally slower,

affected less by temperature variations,

more durable,

can be more difficult to maintain

than Pneumatic systems.

Musk’s humanoid Optimus shows progress

Elon Musk has just tweeted about his humanoid robot Optimus. It seems that the android is now capable of locating his own limbs in space and in connection with this, can learn tasks, even in a changing environment.

The video in Musk’s tweet shows that the android can sort cubes based on their colors by picking them up by its fingers and can do this even when someone keeps changing the location and orientation of cubes deliberately.

At the end of the video, the robot displays some acrobatic moves beautifully…

A very promising video indeed…

Robotic arm gripper key design considerations

The purpose of a robotic gripper is to effectively manipulate and grasp objects.

First of all, the system for gripping must be chosen. Such as two or more finger grippers, parallel jaw grippers, suction grippers and other types. Some grippers are designed for only specific types of objects, which makes the design easier.

Let’s list some key factors to consider:

Gripping force. This should be balanced at each instant and position, in order to be sufficient to hold and manipulate the object but not too much, in order to avoid damage. Dealing with delicate objects is especially a challenge.

Sensors: It is important to get feedback from the object being manipulated in order to manipulate it the desired way. Tactile force and proximity sensors are used.

Control: The control algorithm gets feedback from sensors, and controls the gripping mechanism accordingly, by adjusting the position of the grippers and the force applied by them at each position. Getting feedback and controlling grippers is a loop that constantly become each other’s input.

Actuation system: Based on the chosen gripper system, proper actuation method must be used. Hydraulic, pneumatic, electric and even shape memory alloys are the most common. Speed of manipulation, power usage, accuracy, ease of control are all determining factors here.

Range of motion: The range and size of expected / required manipulation needed is another major criteria. The wider the range of motion and size, the more complex the gripper system and the control algorithm gets.

Operating Environment: This is also a consideration if factors that will affect the operation of grippers, or surrounding items that will be affected as a result if gripper operation exist.

Materials: Strength, stiffness, durability, smoothness/roughness, weight of the gripper materials are considered. The materials must also be compatible for the target range of tasks and the geometric and physical properties of the objects to be handled. Adequate friction between the grippers and handled objects must be ensured. To maximize ease of actuation and minimize power consumption, lightweight materials are preferred unless there is a need for high mass grippers.

Adaptability: The ability to adapt to unexpected irregularities is a desirable feature, which increases the complexity of the system and control.

Connectivity: The gripper connections to robot arm or other surfaces should be as simple as possible and the value of gripper will increase as its ease of connection with different interfaces increase.

Safety: For a safe operation, measures such as impact detection, emergency stop, soft surfaces, should be implemented.

And as always, cost and ease of design, manufacturing and maintenance must be a key criteria.

Improving Stability of Bipedal Robots

When building bipedal robots (robots that walk on 2 legs), ensuring stability is a primary objective.

The following strategies are among the most important:

1- First of all, before even considering the rest, we need to make the physical shape and mass distribution as good as possible for a proper, stable stance. This simply means
-the center of mass is as low as possible, (for example placing heavier components at the bottom and or making upper components of lighter weight material
-the mass is distributed as evenly as possible
-the mass bears on as wide surface area as possible (this can be achieved by positioning and proportioning of sizes of legs and feet accordingly but this will obviously affect maneuverability

These principles are simply following basic physics rules, similar to making buildings stable. If this item is not properly done, the rest below can only go so far, or it will mean difficult and costly/time consuming solutions. This item is similar to an architect designing the overall shape of the building as regularly as possible in the first place, for a smooth and efficient flow of forces from top floors all the way to the foundation. If the architect’s design is irregular there is only so much the structural engineer can do to accommodate those irregularities or the solution will need stronger members, connections and load carrying system, which will be costlier and longer to build.

2- The robot must be able to predict the immediate future situations and adjust controls accordingly.

3-Robots joints (limbs) must be designed to provide a balanced and stable motion. The control algorithm must adjust joint torques instantly to respond to feedback from sensors.

4- Machine learning and adaptation techniques can also be applied. With proper algorithm, by learning from failures, the robot will be able to refine its responses.

5-Sensor inputs must provide adequate information to the robots control algorithm. Sensors inputs such as visual, inertial, force and torque are necessary components.

Also search the term Zero Moment Point (ZMP)

What are co-bots?

Co-bot stands for “collaborative robots”. These robots are designed to work alongside humans, by performing repetitive or heavy tasks, which would greatly ease the burden on the human worker while he or she can focus on tasks that require higher skills.

A critical item for making this possible is to implement certain safety mechanisms on these robots, in order to prevent harm to humans. This can be achieved by certain sensors placed on the robots body, in order to prevent impacts to human workers. These sensors include force, torque and ultrasonic sensors. It is also necessary to cover robots body with soft material.

Working alongside humans means that there will be more unexpected circumstances in robots environment, in comparison to unchanging environments of industrial robots. Therefore, these robots must operate with considerably more complex visual recognition and AI abilities. These robots can also be trained for new tasks by literally guiding them physically in addition to classical programming, which is very intuitive and efficient.

The market of collaborative robots is ever growing, since their beginning about 1-2 decades ago.  

What are co-bots?

Co-bot stands for “collaborative robots”. These robots are designed to work alongside humans, by performing repetitive or heavy tasks, which would greatly ease the burden on the human worker while he or she can focus on tasks that require higher skills.

A critical item for making this possible is to implement certain safety mechanisms on these robots, in order to prevent harm to humans. This can be achieved by certain sensors placed on the robots body, in order to prevent impacts to human workers. These sensors include force, torque and ultrasonic sensors. It is also necessary to cover robots body with soft material.

Working alongside humans means that there will be more unexpected circumstances in robots environment, in comparison to unchanging environments of industrial robots. Therefore, these robots must operate with considerably more complex visual recognition and AI abilities. These robots can also be trained for new tasks by literally guiding them physically in addition to classical programming, which is very intuitive and efficient.

The market of collaborative robots is ever growing, since their beginning about 1-2 decades ago.  

Optimizing mobile robot power efficiency

Optimizing mobile robot power efficiency

The basic physical body of the robot should be understood and optimized first. Robot should be as lightweight as possible, unless high mass (for weight or inertia) is needed for a specific reason. Friction between moving parts should be minimized except for the parts that need a certain amount of friction.

The components must be energy efficient, such as motors, sensors, microcontrollers.

Sensor data should be obtained and processed efficiently, to avoid unnecessary data and processing. For this, data from multiple sensors should be efficiently integrated. Also see “sensor fusion”

Some tasks use a lot of power such as image processing, analysis of input data, navigating environment and avoiding obstacles. Algorithms for these should be optimized. For example, while navigation environment, the shortest path that involves the least obstacles will mean less energy usage. Data compression alsohelps save power during processing.

Using smart battery usage optimization / management systems, including real time monitoring of performance that can identify areas for improvement

Optimized wireless communication is a good way to save power. This should be used as much as possible.

Robot’s movements should be kept at a minimum, as long as the desired objectives are reached. In other words, efficient motion planning where only essental tasks should be performed when and where necessary by prioritizing tasks.

Some components are not always in use. They should have sleep or low power mode.

Using kinetic energy recovery systems

Making use of solar power is always a good idea, if available area and weight problems can be solved.

Some tasks can be taken care of with multiple / swarm robots better.

Modelling of a Transport Robot Fleet in Simulink

InSystems and Model Engineering Solutions jointly developed a Simulink model of an adaptive fleet of InSystems’ proANT collaborating transport robots. The goal was to capture the desired adaptive system behavior to more effectively deal with the typical goals and challenges of collaborative embedded system groups (CSGs). A fleet of robots has to react to dynamic changes in the policy of the manufacturing execution system or the number and nature of its members to safeguard its functionality. The consistent application of a model-based development process for automation systems offers a variety of benefits to deal with these challenges. First and foremost, the specification of the CSG in the form of executable models allows for a fully virtual simulated representation of the robot fleet. This provides a sound foundation to efficiently develop and maintain the actual system. To exploit the full potential, a model-based approach relies on the reusability of models and test beds throughout the different development phases. Secondly, the model-based development process profits from a fully integrated tool chain that highly automatizes associated development activities. These include requirements management, modelling, and simulation as well as integrated quality assurance tasks, most notably, model-based static analysis and requirements-based testing. Tools such as the MES Model Examiner® and the MES Test Manager® are beneficial in streamlining the process.

Abbildung 1: Figure 2: Fleet of proANT AGVs at Bierbaum Unternehmensgruppe, transporting open barrels.
Image Source: Model Engineering Solutions – GmbH

The post Modelling of a Transport Robot Fleet in Simulink appeared first on Roboticmagazine.

Autonomous Navigation

To navigate its environment, a robot must be either remote controlled, preprogrammed in a known unchanging environment, or it must be able to do this autonomously. To be able to navigate autonomously a robot must be able to not only continuously model and update its environment, which can be static and dynamic, but also be able to determine the best path to take based on this model and its own instantaneous location. Based on this model, the navigation algorithm must be able to predict the future states of all the obstacles and objects in the environment. The necessary inputs to overcome these challenges are obtained through sensors, mainly camera but can involve other sensors such as infrared, ultrasonic, LiDAR and more.

Although the background was laid before, the technology saw fast improvement after 2000s. DARPA Grand challenge for autonomous vehicles for example, took it one step ahead each year, until finally it was discontinued due to completion of a path in its entirety was not a challenge anymore. Today we see autonomous navigation technology in cars, trucks and other robotic systems including humanoid robots (androids), various domestic robots such as security, delivery, warehouse robots, to varying degrees. Once full autonomy in traffic is achieved as a widespread application, the technology is expected to transform our life in various ways.

Post Date: December 7th, 2022

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