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Scratch is extremely popular among budding roboticist , and for good reasons. The visual programming language essentially involves dragging and connecting blocks. Furthermore, Scratch is the language of choice in most robotics clubs and school technology classes. Most experienced roboticists are unlikely to write any industrial robots in Scratch.
However, the language provides a useful way for beginners to get into robotics. Today, almost every robot comes with its proprietary robot programming language.
As you may have guessed, that has been a long-standing issue in industrial robotics. It means users have to learn a new language every time they use a new robot brand. The list goes on. Some general-purpose programming framework — such as ROS Industrial — are starting to offer standardized options. However, technicians are still likely to use the proprietary language. The field of artificial intelligence has become more popular recently.
As a result, various AI programming languages are now enjoying more attention than ever before. LISP and Prolog are two of such languages. LISP is one of the earliest programming languages. As a result, it pioneered many ideas in computer science, such as automatic storage management, conditionals, recursion, and higher-order functions.
Meanwhile, Prolog was one of the first logic programming languages. Besides proving useful for natural language processing , Prolog is also used for theorem proving, expert systems, and automated planning. Indeed, you can program artificial intelligence using other languages on this list.
Engineers who create low-level electronics for robots use Hardware Description Languages to describe their prototypes. Thanks to HDL , programmers can quickly describe a circuit using words and symbols. Development software can then convert that textual description into configuration data for implementation. Aside from data processing, some university courses also use this programming language for research purposes.
These include:. C is a proprietary programming language from Microsoft. As such, researchers that want to use the system must learn C. Besides, the programming language also serves as the basis for some popular Virtual Reality engines such as Unity. With that said, C may not be the most straightforward programming language to learn.
Java is a class-based, object-oriented, general-purpose, programming language. As such, it becomes possible to use the same code on different machines. JAVA is quite useful is some aspect of robotics. Python is one of the most popular programming languages, thanks to the fast-growing machine learning field. The significant advantage of this programming language is its ease of use. With Python, things that take up time in programming — such as defining and casting variable types — becomes unnecessary.
Besides, an extensive amount of free libraries are available for Python. Robots, like people, need a purpose in life. The goal of our software controlling this robot will be very simple: It will attempt to make its way to a predetermined goal point.
This is usually the basic feature that any mobile robot should have, from autonomous cars to robotic vacuum cleaners. The coordinates of the goal are programmed into the control software before the robot is activated but could be generated from an additional Python application that oversees the robot movements. For example, think of it driving through multiple waypoints. However, to complicate matters, the environment of the robot may be strewn with obstacles.
Therefore, if the robot encounters an obstacle, it will have to find its way around so that it can continue on its way to the goal. Every robot comes with different capabilities and control concerns. The first thing to note is that, in this guide, our robot will be an autonomous mobile robot.
This means that it will move around in space freely and that it will do so under its own control. This is in contrast to, say, a remote-control robot which is not autonomous or a factory robot arm which is not mobile. Our robot must figure out for itself how to achieve its goals and survive in its environment.
This proves to be a surprisingly difficult challenge for novice robotics programmers. There are many different ways a robot may be equipped to monitor its environment. These can include anything from proximity sensors, light sensors, bumpers, cameras, and so forth. In addition, robots may communicate with external sensors that give them information that they themselves cannot directly observe. There are more sensors facing the front of the robot than the back because it is usually more important for the robot to know what is in front of it than what is behind it.
In addition to the proximity sensors, the robot has a pair of wheel tickers that track wheel movement. These allow you to track how many rotations each wheel makes, with one full forward turn of a wheel being 2, ticks. Turns in the opposite direction count backward, decreasing the tick count instead of increasing it. Later I will show you how to compute it from ticks with an easy Python function.
Our robot is a differential drive robot, meaning that it rolls around on two wheels. When both wheels turn at the same speed, the robot moves in a straight line. When the wheels move at different speeds, the robot turns. Thus, controlling the movement of this robot comes down to properly controlling the rates at which each of these two wheels turn.
This interface internally uses a robot object that provides the data from sensors and the possibility to move motors or wheels. If you want to create a different robot, you simply have to provide a different Python robot class that can be used by the same interface, and the rest of the code controllers, supervisor, and simulator will work out of the box! As you would use a real robot in the real world without paying too much attention to the laws of physics involved, you can ignore how the robot is simulated and just skip directly to how the controller software is programmed, since it will be almost the same between the real world and a simulation.
But if you are curious, I will briefly introduce it here. The file world. The step function inside this class takes care of evolving our simple world by:. The step function is executed in a loop so that robot. The same concepts apply to the encoders. First, our robot will have a very simple model. It will make many assumptions about the world. Some of the important ones include:. Although most of these assumptions are reasonable inside a house-like environment, round obstacles could be present.
Our obstacle avoidance software has a simple implementation and follows the border of obstacles in order to go around them. We will hint readers on how to improve the control framework of our robot with an additional check to avoid circular obstacles. We will now enter into the core of our control software and explain the behaviors that we want to program inside the robot. Additional behaviors can be added to this framework, and you should try your own ideas after you finish reading!
A robot is a dynamic system. The state of the robot, the readings of its sensors, and the effects of its control signals are in constant flux. Controlling the way events play out involves the following three steps:. These steps are repeated over and over until we have achieved our goal.
The more times we can do this per second, the finer control we will have over the system. The Sobot Rimulator robot repeats these steps 20 times per second 20 Hz , but many robots must do this thousands or millions of times per second in order to have adequate control.
Remember our previous introduction about different robot programming languages for different robotics systems and speed requirements. In general, each time our robot takes measurements with its sensors, it uses these measurements to update its internal estimate of the state of the world—for example, the distance from its goal.
It compares this state to a reference value of what it wants the state to be for the distance, it wants it to be zero , and calculates the error between the desired state and the actual state. Once this information is known, generating new control signals can be reduced to a problem of minimizing the error which will eventually move the robot towards the goal.
To control the robot we want to program, we have to send a signal to the left wheel telling it how fast to turn, and a separate signal to the right wheel telling it how fast to turn. However, constantly thinking in terms of v L and v R is very cumbersome. Mission Omega - C64 and Amstrad?
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