A robot will require a programming language for describing the operations that are to be done. Recently, there are plenty of robot programming languages available. Among them, five robot languages are commonly and basically used. They are:
RAIL
AML
VAL
AL
RPL
RAIL:
RAIL will be a best language for controlling two major tasks such as the manipulation and visionsystem. It is a high – level robot language based on Pascal, and it will implement a Motorola–68000 central processor, teach pendant, and terminal. This language was designed by Automatix for arc welding and inspection purposes.
RAIL comes with three different kinds of systems, namely:
Hitachi Process Robot – Arc Welding
Cartesian Arm – Assembly functions
Vision system without arm
AML:
AML (A Manufacturing Language) is a high level language based on sub routine, which is mainly implemented to manage RS / 1 Assembly Robot, End Effectors Active Force Feedback, and Cartesian Arm with hydraulic motors. The RS / 1 assembly robot incorporates a mini – computer (IBM Series/1), 192 KB memory, matrix printer, disk drive, display terminals, and keyboard. AML was developed by IBM Corporation for robot programming. An important reason for creating this language is to offer simple subsets and as well as powerful base language.
VAL:
VAL (Variable Assembly Language) Robot Programming Language is adopted mainly forUnimation Robots. As this language is designed with simple syntax, it is capable of illustrating the robot functions very easily. It includes two major tasks such as:
Program instructions are used to provide VAL programs in order to manage the robot functions.
Monitor commands are used to execute the user written programs.
AL:
AL robot language was developed in Artificial Intelligence Lab at Stanford University. It is the second generation language based on simultaneous Pascal. The programs are written and executed on PDP – 10. If the program is developed with high level code, then it should be written in Stanford Artificial Intelligence Language (SAIL). The AL system includes a big mainframe computer, and it generally runs on PDP 11/45. The PDP 11/45 implements one terminal, 128 KB RAM memory, and floating point processor. This language has got the capability to control two Stanford Scheinman and two PUMA 600 arms simultaneously.
RPL:
RPL robot language makes the improvement, checking, and correction of control algorithms very easy. It can be done even by an unskilled programmer like line foreman, production engineers, etc. The RPL programs are translated to interpretable code with the help of a compiler in SRI Robot Programming System. The programs are typically written in BLISS – 11 and run in RT – 11. The DECPDP – 10 is cross compiled into the LSI – 11 or PDP – 11. This robot language was designed in SRI International.
RankBrain is the newest A.I. system to respond to a series of queries. In June, Google trained a computer to have conversations with people by asking it questions about technical support, common knowledge and philosophy. It was called “conversation model” and was developed by research scientists at Google Brain.[1]
The research scientists used a sequence-to-sequence framework in the exercise, which converses by predicting what the next sentence will be in a dialogue. The device predicts what the next question will be by drawing upon data provided by IT helpdesk manuals, book quotes, subtitle data bases and more.[2]
For example, during a technical support question, the machine was able to diagnose why the browser of a computer crashed. It was then asked a wide range of questions, some of which were common, while others, profound.
The computer registered fairly good results when asked about common knowledge questions, such as recognizing who Luke Skywalker was, whether a cat can fly and whether the sky was blue.[2]
On the other hand, the computer had mixed results when it came to answering existential questions pertaining to the human condition. For instance, when the computer was asked what the purpose of life was, it responded, “to serve the greater good and to live forever.” Nevertheless, when the machine was asked to provide a definition of morality, it responded, “I don’t have ethics.”[2]
The machine had trouble identifying with human emotions too. It stated having a child was immoral. When pressed to provide a definition of altruism, the machine seemed confused and replied, “If you don’t believe in God, you don’t know.”[2]
It also failed to answer simple math questions and claimed that a spider has three legs.
Preliminary trials aside, RankBrain is now the third most important signal which determines what search results a user views.
The goal was bit optimistic for the time given, but still, using also some additional time until the end of the event (hackathon took place on the 1st day), I managed to build the social-dancing Robot that was demonstrated during the closing of the event:
The idea was to make the robot more IoT-enabled and interactive with the audience. So, I built a webpage that runs on a smartphone and gets events from the tilt sensor of the phone and delivers a dancing command to the robot through MQTT. When more than 2 people use the webpage and tilt (dance with) their phones, the command changes, and the robot performs a different-better type of dance.
R2-D2. GERTY 3000. Marvin. K-9. Jinx. These are just a few of the most well-known robotic sidekicks that super geeks like us have come to love over the years. Soon, PLEN2 may join the ranks of these memorable sci-fi characters, with the only difference being actual use in the real world. Whether you’ve ever wanted someone to go to class in your place, to break the ice with an attractive girl at the bar, or to fetch your morning cup ‘o joe, you’re in luck.
Launched on Kickstarter by Japan-based PLEN Project Committee, the 3D-printable, humanoid robotic kit consists of a control board, servo motors and other electronic accessories that allow Makers of all levels to put together themselves. What’s more, you don’t need any technical knowledge or special tools in order to bring your open-source PLEN2 to life.
3D data for the main components of the robot are provided free of charge, and with the help of a 3D printer, users can customize the data as well as make their own original parts. Upon completion, the easy-to-manuever and highly-agile humanoid stands approximately 7.87” tall, weighs just over 21 ounces and boasts 18 degrees of freedom. Designed to mirror its human counterpart, PLEN2 aspires to revolutionize the relationship between homo and robo sapiens. To help spur this adoption, the project’s creators have made its kit super simple to assemble, personalize, and of course, use.
The robot’s command center is built around an Arduino Micro (ATmega32U4), and by employing some open-source software, can be programmed to meet any Maker’s wants and needs. PLEN2 is equipped with 24 RC servo motors, 1Mb of on-board EEPROM and an RS-485 communication port in both its control and head board. The head unit also comes standard with a BLE113 Bluetooth Smart module and a six-axis motion sensor, while PWM will drive the LEDs that PLEN2 uses for eyes.
Gadget-lovers can take pleasure in knowing that each PLEN2 can be customized not only in color and design, but in the way that it is controlled as well — this includes by iOS or Android smartphone, facial expression, gestures, myoelectrics and brainwaves, among countless other input methods.
Not only for leisure activities, the humanoid can play an integral role in both educational and medical settings. A wide-range of uses cases include communicating with others in your place, carrying small items around, throwing a pickup game of humanoid soccer, as well as improving medical rehabilitation. What’s more, it can help entice children to pursue STEM disciplines and enable them to experience the joy of making things themselves.
As to whether this project takes off, or if you decide on programming a PLEN2 of your own, one thing is certain: Its theme song will get stuck in your head. Consider yourself warned…
…We told you so. Interested in learning more? Head over to its official Kickstarter page, where its team is currently seeking $40,000. If all goes to plan, you can have can have a PLEN2 alongside of you come November 2015.
Language is a distinctly human, innate mental structure. It is a prime example of a mental algorithm, which strings words into new combinations by plucking them from a memory bank. Recently, scientists have replicated this mental algorithm by developing an artificial intelligence (A.I.) software, which has the language skills of a four-year-old.
The machine mirrors the way a human brain functions. It was given 1,500 sentences from literature about language structure. It then drew from these words in order to sew new conversations together as the machine spoke with people.
The sentences didn’t flow out of the program naturally, but had the occasional hiccups of a typical A.I. program. The researchers claim the computer, dubbed Artificial Neural Network with Adaptive Behaviour Exploited for Language Learning or ANNABELA, had the language capacity of a four-year-old.
TALKING THE TALK
While having a dialogue with an adult, ANNABELA was able to churn out 500 sentences. The computer reflected the way children learn to speak by listening to their parents and understanding how words are used in specific contexts.
According to Dr. Bruno Golosio, a computer scientist at the University of Sassari in Italy, “The system is capable of learning to communicate through natural language starting from tabula rasa (blank slate), without any a priori knowledge of the structure of phrases, meaning of words, role of the different classes of words, only by interacting with a human through a text-based interface, using an open-ended incremental learning process.”
“It is able to learn nouns, verbs, adjectives, pronouns and other word classes, and to use them in expressive language,” he added.
What is unique about ANNABELA is that instead of having a pre-coded knowledge of language, as is the case with other speech recognition programs, the machine starts off with a blank slate. Researchers from the University of Sassari in Italy and the University of Plymouth in the UK orchestrated the system by weaving together two million artificial neurons.
It is hoped this artificial tapestry of neurons will enable A.I. systems to become more human-like, as portrayed in various Hollywood films. ANNABELA reflected the brain’s plasticity, which refers to the brain’s ability to form new connections between neurons. The brain is not cemented in time, but can morph and change throughout life.
The researchers breathed 1,587 sentences drawn from literature into the system, in order to assess the development of language in children. They asked the machine various questions a typical four-year-old could answer, such as “What is your father like?” and “How many games do you play?”
MACHINES THAT THINK
The study was published in the journal Public Library of Science One. The researchers claimed the system learned how to count, understood the concept of a friend and was able to execute personal pronouns like “her.”
Cognitive scientists are interested in understanding how language develops in order to catch a glimpse into the window of the human mind. In fact, some schools of thought even suggest we wouldn’t be self-aware in the first place without language.
In particular, a toddler develops a sense of self by executing referential pronouns like myself. It is a piece of grammatical English used to express a reflexive form. Without self-referential pronouns, so it is argued, we would be aware, but we wouldn’t be self-aware. In other words, we would be autopilot objects projecting into to the void.
If ANNABELA indeed has a sense of self, it is yet a very crude sense of self currently unworthy of the name. Nevertheless, the A.I. system is a remarkable achievement, as it illustrates that, at least, some mental structures can be replicated.
In a joint effort started in 1995 the United Nations Economic Commission for Europe (UNECE) and IFR engaged in working out a preliminary service robot definition and classification scheme, which has been absorbed by the current ISO Technical Committee 184/Subcommittee 2 resulting in a novel ISO-Standard 8373 which had become effective in 20121. A preliminary extract of the relevant definitions is given here:
A robot is an actuated mechanism programmable in two or more axes with a degree of autonomy, moving within its environment, to perform intended tasks. Autonomy in this context means the ability to perform intended tasks based on current state and sensing, without human intervention.
A service robot is a robot that performs useful tasks for humans or equipment excluding industrial automation application. Note: The classification of a robot into industrial robot or service robot is done according to its intended application.
A personal service robot or a service robot for personal use is a service robot used for a non-commercial task, usually by lay persons. Examples are domestic servant robot, automated wheelchair, personal mobility assist robot, and pet exercising robot.
A professional service robot or a service robot for professional use is a service robot used for a commercial task, usually operated by a properly trained operator. Examples are cleaning robot for public places, delivery robot in offices or hospitals, fire-fighting robot, rehabilitation robot and surgery robot in hospitals. In this context an operator is a person designated to start, monitor and stop the intended operation of a robot or a robot system.
A robot system is a system comprising robot(s), end-effector(s) and any machinery, equipment, devices, or sensors supporting the robot performing its task.
Please note: According to the definition, “a degree of autonomy” is required for service robots ranging from partial autonomy (including human robot interaction) to full autonomy (without active human robot intervention). Therefore, in addition to fully autonomous systems service robot statistics include systems, which may also be based on some degree of human robot interaction or even full tele-operation. In this context human robot-interaction means information and action exchanges between human and robot to perform a task by means of a user interface.
With this definition, manipulating industrial robots (which can be either fixed in place or mobile) could also be regarded as service robots, provided they are installed in non-manufacturing operations. Service robots may or may not be equipped with an arm structure as is case with some industrial robots. Often, but not always, service robots are mobile.
In some cases, service robots consist of a mobile platform on which one or several arms are attached and controlled in the same mode as the arms of industrial robot. Furthermore, contrary to their industrial counterparts, service robots do not have to be fully automatic or autonomous. In many cases these machines may even assist a human user or be tele-operated.
Due to their multitude of forms and structures as well as application areas, service robots are not easy to define.
World Robotics Survey: Industrial robots are conquering the world
Frankfurt, 30 September 2015 – By 2018 global sales of industrial robots will on average grow year on year by 15 percent – the numbers of units sold will double to around 400,000 units. Five major markets representing 70 percent of the total sales volume: China, Japan, USA, South Korea and Germany. So says the 2015 World Robot Statistics, issued by the International Federation of Robotics (IFR).
“The main driver of this development is the global competition of industrial production. The automation witnessed by the automotive sector and the electrical/electronics industry comes out top here with a market share of 64 percent”, says Arturo Baroncelli, President of the International Federation of Robotics (IFR).
Within this context, the rapid automation in China represents a unique development in the history of robotics. The number of industrial robots sold increased by 56 percent alone last year in comparison to 2013. China is the largest and fastest growing robotics market in the world. The potential remains enormous despite the recent economic downturn. After all Chinese production industries currently have a robotic density of just 36 units per 10,000 employees. To compare: As the front-runner South Korea deploys 478 industrial robots per 10,000 employees followed by Japan (315 units) and Germany (292 units). It is estimated that more than one-in-three of the global supply of industrial robots will be installed in the Republic of China in 2018.
The statistics on robotic density likewise indicate huge opportunities for growth in the USA. Production industries there deploy just 164 industrial robots per 10,000 employees right now. The USA is currently automating its economy at high speed. The aim is to strengthen the country as an industrial centre and to retrieve outsourced production. In 2014 the number of installed robots increased by 11 percent to around 26,000 units – making it third in the world.
In Europe it is Germany that takes the lead by some distance. Within one year (2014) the sales figures increased by around 10 percent to about 20,100 units – to date the largest number of sales registered within twelve months. Despite the already very high robotic density existing there, the world’s fifth largest robotics market remains on a path of expansion – driven primarily by the automotive industry.
Global investments made by the automotive industry in industrial robots have increased significantly since 2010. 2014 was a new record year with about 100,000 newly installed robots – up 43 percent compared to the previous year. This boom has been fuelled by new production capacities in emerging markets and a wave of modernisation sweeping through established auto-making countries. A large proportion of robotics technology in 2014 was purchased by suppliers of electronic components to the automotive industry. These include battery manufacturers and car IT enterprises.
In 2014 the electrical/electronics sector likewise posted a new record – sales increased by 34 percent compared to the previous year. The strong demand for industrial robots in the production of consumer electronics, communication equipment as well as computer and medical technology adds up to a total global market share of 21 percent.
The wave of digital transformation and automation will continue to drive the triumphant march of industrial robots onwards up to 2018. “Industry 4.0” projects mean that human-robot teams, for example, are on the cusp of a break-through. Simplification of the use of robots will additionally open up the market for new applications. This is equally true of small and medium-sized companies as it is for large corporations in all sectors. Besides the automotive and electronics industries, this development is also being increasingly felt in the metal processing, plastics, food and packaging industries.
“The market volume available to industrial robots is enormous. Including supporting services we estimate the global market value to be 32 billion US dollars for 2014”, sums up IFR President Baroncelli.
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With Robotmaster, manufacturers can program robots quickly and efficiently, using industry proven CAD/CAM software technology. Driven by the growing trend towards lean and flexible manufacturing, robots are progressively replacing conventional dedicated manufacturing units, such as CNC milling machines. Robots, once perceived as only positioning devices, have advanced in accuracy and rigidity, and are now being used increasingly for manufacturing and material removal. With industrial robotics, manufacturers are producing higher quality products at lower cost, and are achieving the speed and flexibility they need to challenge their competitors throughout the world.
According to the International Federation of Robotics as of 2013 over 1.5 million robots were estimated to be in operation in industrial applications worldwide, and an additional 160,000 are being sold every year. While many companies currently using CNC machines have been exploring the opportunity of manufacturing with the use of industrial robotics, they have been limited by a lack of time and cost-effective robotic programming tools. Currently less than 1% of robots are programmed using CAD/CAM (computer aided design and manufacturing) software because of a lack of mature robotic programming solutions. Robotmaster eliminates this barrier.
Robotmaster delivers:
Cost-efficiency and flexibility of robots coupled with the ease of programming.
Programming of robots from CAD/CAM software as easy as CNC machine programming.
A sure way to beat the competition -worldwide- on cost, flexibility and response time.
Revolutionary CAD/CAM approach to robot programming software
Our strong background in CAM (Computer Aided Manufacturing) software has enabled us to bring a revolutionary approach to programming for industrial robotics. Unlike the wide range of simulation software packages that claim to be off-line programming for robots while truly only offering very limited programming capability, Robotmaster delivers easy programming of precise tool motion control and quick generation of long tool path trajectories with minimal programmer intervention.
Robotmaster uses mature CAD/CAM software technologies for robotic programming with the same flexibility and speed as software used for programming CNC machine tools. Conventional off-line robot software programming solutions are based on either a very cumbersome and tedious point to point programming approach or a post-processor solution that offers very little flexibility and functionality.
Robotmaster CAD/CAM programming:
Generates more profit with your robot. Robotmaster generates programs off-line and eliminates lost production time during programming.
Delivers closest conformance to design. Robotmaster creates simple or complex robot trajectories accurately without teaching points.
Integrated robot programming software solution
Robotmaster seamlessly integrates programming, simulation and program generation to any CAD/CAM platform. The multi-software approach of conventional off-line robot software solutions forces the use of one software for CAD/CAM programming, another for converting trajectories to robot positions and finally a third to simulate and validate the programmed trajectories.
Robotmaster Integrated Solution
Multi-software Approach
Integrated programming produces:
Quicker robot programming, validation and code generation.
Easy program updates and revisions.
Evolution of robot programming
Using MANUAL TEACH PENDANTS, robots “learn” from the operator jogging the robot through the trajectory and recording points, one point at a time, using the robot’s teach pendant. Robotmaster takes the process off-line and engineers the robot program from the design drawings.
OFF-LINE EMULATORS reproduce the manual teach process in an off-line setting, using a simulation software environment in place of the robot’s teach pendant. Robotmaster follows the path-intensive CAD model accurately and automatically and permits easy updating and revision of the program.
GENERATION 1 OFF-LINE SOFTWARE provides a CAD software environment for manual input of robot parameters for every point of a desired path, one at a time, on a CAD model. Robotmaster automatically generates the full robot trajectory from any CAD/CAM tool path strategy in a fraction of the time.
GENERATION 2 OFF-LINE SOFTWARE generates a robot trajectory by following trajectories drawn manually within a CAD modelling software. Robotmaster automatically generates the full robot trajectory from any CAD/CAM tool path strategy, building direct links between the CAD model and the tool path, without the need to manually draw any additional geometry.
A CAD/CAM POINT CONVERTER is a CAD/CAM post processor, robot simulator utility or standalone software that converts tool path output by CAD/CAM software into a robot trajectory for a specific model or brand of robot. Robotmaster is a fully integrated solution that permits seamless interaction between CAD/CAM and robot programming functionality, allowing trajectory optimization and integrated robot kinematics and simulation for a wide portfolio of robot models and brands.
Solving programming challenges
Struggling to program a robot the way you do a CNC machine tool? Robotmaster is up to the challenge:
Not easy to check intuitively robot joint limits and robot-to-part collisions?
Robotmaster automatically checks programs for joint limits, robot reach limitations and collisions.
Need to do manual touch-up and rework of your off-line programmed points?
Robotmaster inherently calculates robot joint values and properly sets parameters to give seamless program playback without manual intervention.
CAD/CAM data is not enough to provide position and orientation data for a 6-axis robot?
Robotmaster uses automated settings for orienting the robot tool to manage trajectories with complex orientation changes.
Your program produces errors and stops running when it passes through one of your robot’s singularity zones?
Robotmaster checks for singularity and has powerful tools to correct programs containing singularities.
How to select from the up to 8 possible configurations that your robot has to achieve everyone of its programmed points?
Robotmaster can vary configurations for optimal programming of trajectories or follow your specific robot configuration choice.
Inaccuracies in your part or tool setup cause production delays as you make manual adjustments?
Robotmaster eliminates adjustments and increases program accuracy by calibrating the physical part and tool setup with the virtual CAD model.
REFERENCE
Billard-handbook
We are indebted to them and the sharing is non commercial
Remote Control Robotics
Some may argue that a robot is not really a robot if it isnt autonomous. Maybe it is or maybe it isn’t. Point being, those some are morons. Learning how to implement remote control features into a robot is a very important skill in robot making. To justify it, I will quickly go over robot intelligent control methods . . .
Introductory to Robot Intelligence
There is actually a spectrum for robot intelligence. Fully remote control and fully autonomous are not your only options. Instead you should decide what level of intelligence you wish your robot to have. Generally assume the more intelligent, the more difficult to build.
Here are the main categories:
Automaton ‘Intelligence’
The lowest level of robot ‘intelligence’ is a simple automaton device. My definition of an automaton is a device where there is absolutely zero decisions made no matter the given environment. They are simple devices where the action it does is repetitive and automatic. A simple circuit with a motor or a combination of gears and a spring could easily be an automaton. Ever hear of those ‘robots’ from the 1800’s that apparently can write names and poems and other useless stuff? They were very well designed gear integrations. However these ‘robots’ would keep writing even if the ink well ran out of ink . . . The device simply has no fault tolerance, and will continue attempting the action. They did not even have a method to sense the environment – a requirement of decision making. BEAM ‘robots’ basically fall into the same category, except they are made from very well designed electronics instead of gears.
Remote Control ‘Intelligence’
Remote control is the next level of robot ‘intelligence.’ Our current technology is capable of building so many machines physically capable of so much more than any lifeform on our planet. Our planes fly many times the speed of sound, our everyday cars can cross the Sahara Desert in days, but our best computers cannot even match a roach brain in terms of autonomy. Solution? Put the human brain in the driving seat of our machines. This allows for the best of both worlds. Strength and expendability of a machine, brain of a human. Battlebots is a perfect example.
Teleoperation
Teleoperation is one step above remote control. The advantage a computer has over the human brain is speed. A typical home computer today can crunch more numbers in a few seconds than a human can in an entire lifetime. But despite that speed, the computer does not have a good understanding of the situation. Added to that, our most advanced electronic sensors cannot match our human eyes and ears for observing the situation. Solution? Let the human make the decisions, but have the computer carry them out. A perfect use for this would be a robot spider. A human operator in no way can control 8 legs with 3 joints each. Instead, the human would give commands like ‘go forward’ or ‘rotate’ and the computer will handle the rest. This method is also very common with space robots because of the long transmission delay.
Full Autonomy
Fully autonomous robots are still a dream. It is a huge area in current state-of-the-art robotics research. It concerns artificial intelligence, consciousness, advanced sensory percerption . . . the list goes on. Huge philosphical implications as well. But all this is out of the scope of this tutorial. If you make a robot that can intentionally navigate from your couch to your kitchen and back without any collisions all by itself, you have built an autonomous robot. But if it fails to bring a beer back you are still a beginner in my eyes . . .
How to Build a Remote Control Robot
The remote control robot is probably the easiest of all robots you can make. A complete beginner can probably make a basic remote control robot in under an hour. The electronics part is plug-n-play, the robot chassis being what will take a little time. Remote control robotics is great for those who want to build a robot – yet does not have enough time, skill, and/or patience to so see a large project through to completion. Have a look at an example of a wall climbing robot with an arm.
First, a video to help you get started:
All you need is a few cheap commercially available items:
Remote Control Transmitter
The remote control transmitter is the handheld thingy with knobs and buttons and a long intenna sticking out of it. This will be the most expensive part you need to buy, around $40-$200. It will require it’s own battery and battery charger. The remote control transmitter usually has very good range. Once as a test, I put my robot in the basement of a building, climbed to floor 10, then operated it without any issues. If you plan to ever do USAR (Urban Search and Rescue), this is a useful feature. The most important feature you need to be concerned with is number of channels it can operate on. Each channel allows you to control one more item on your robot. I recommend at least three, but I have often used up to six on a single robot in the past.
Receiver
The receiver is a small little box thingy that you put on your robot. It accepts the signal from your transmitter, processes it, then outputs a servo ready signal. This will be the second most expensive part, usually around $30-$60. It will require around ~5V to power it.
Receivers can get really small:
If you want to use a higher voltage for the servos, get something called a Y-harness (see below image).
You simply attach it to a servo port, and then attach your higher voltage batteries and your servo to the other end. Read the instructions for power! Like with the transmitter, you must be concerned with how many channels you would like to have.
Operating Frequency Crystal
Both your transmitter and your receiver will each require a crystal. These are necessary to ensure both of your devices are operating under the same frequency (so purchase both crystals with the samechannel!!!). For RC, there are two frequencies you need to be aware of. One is for air and one is for surface. Remember, its illegal and bad practice to control a remote control car with an air frequency. You could accidently cause someone’s remote control aircraft to crash and kill some poor cute innocent squirrel! But you already knew that . . . When you purchase your receiver/transmitter, they will specify whether it should be used for air or surface RC. Another note, the crystal is fragile. If your remote control vehicle crashes a lot, the crystal could get damaged. I once made a robot for a USAR competition that was designed to handle 7 foot drops. But apparently the crystal was not. It broke. Sadness. The solution? Receivers often come with a foam padthingy to wrap it in for shock absorption. If not, find some foam padding and use it. The crystals usually come as part of your transmitter and receiver, but if not, or if you break one, they cost like $8 plus shipping to replace.
The materials above are the basics required for remote control, but you are not yet done. You now need a few more things to build the robot chassis:
Optional: Robot Frame Material
HDPE
and/or
aluminum
should be used for the frame. Want to build it in 5 minutes? A simple square sheet of HDPE with
all
parts velcroed on will actually work! But you should attach everything more permanantly for a well designed robot.
Optional: Servos
Servos, although not required, are designed to be used with remote control vehicles. All you do is literally plug it straight into your receiver and it instantly works. Get two servos – one for each side of your robot – so that you have differential drive. Put a castor in back for balance. You can also use additional servos for other things such rotating a camera, lifting a shovel, or operating a robot arm. If you are on a strict budget, I highly recommend the Hitec HS-311 servos. They only cost about $8 and work really well for what you need. But of course, the $30 servos work even better . . . And here is how to mount servos onto a robot chassis.
Optional: Teleoperation
Now you do not need a microcontroller for any basic remote controlled robot. But if you want it teleoperational, you must have something to process your commands. So how does this work? The basic concept is
– send a command with the transmitter to the receiver
the receiver then outputs a servo square wave
a simple resistor capacitor circuit changes this square wave to an analog value
and then an analog port on your microcontroller interprets this analog value into a particular command, based upon your written program.
The servo signal to analog signal converter circuit:
Optional: High Power Motor Driver / Speed Controller
If you want a high powered robot that uses something much more powerful than hobby servos, you would instead want a motor driver. Most on the market should directly accept a signal made for a servo, and convert that to what you would need for DC motors. Just hook this device up to your receiver, and attach your motors and battery to it, and by happy squirrels you have an instant Battlebot. Be aware that these can get a little expensive, and many are only capable of handling a single motor – meaning you would need to buy two.
Optional: Speed Controller
The speed controller is basically an H-bridge that operates by a remote control signal. Plug one wire into the receiver, two onto the battery leads, and two on the motor leads – and wallah its controllable by your transmitter. If you wanted to build a fast dc motor driven remote control vehicle, or perhaps need a motor to drive the weapon of your battle bot, this is the way to go.
Last Step: Assembly of your Remote Control Robot
I figure the best way to explain this is to show an example. This particular robot was made by me and a friend in less than 5 hours back in early 2003. It uses somewhat expensive lexan plates, a lego castor, and super glue, double sided sticky tape, and velcro to connect everything together. Ghetto, yes. But it held together really well and was easy/quick to make.
It was designed to play soccer, but since I lived in Pittsburgh at the time there was also plenty of snow to shovel . . . Here is a video of it in action:
And here are two teams of remote controlled
soccer robots all made in the same fasion:
Radio Frequency Reference Chart
On rare occasions you may want to know what frequency you are broadcasting on, and not just which channel it is. For example, if your remote control robot is for an underwater environment, you would want the lowest frequency possible to minimize attenuation (interference).
72 megahertz, Channels 11 – 60: This is the most popular choice for flying models. Most radios designed for model aircraft and helicopters will be available on these channels. DO NOT use this frequency for anything other than aircraft, as you could unintentionally cause a crash of someone else’s remote control aircraft nearby. Big deal? Not so big when they lose hundreds in $$ from damage, or even worse, a death or injury results from the crash . . .
75 megahertz, Channels 61-90: Cars, boats, and other non-flying models must use one of these channels. Pistol grip radios are available on 27 MHz as well as 75.
27 megahertz, Channels A1-A6 and 50 megahertz, Channels 00-09: While legal for air or surface use, we recommend that 27MHz be used only for surface models. A pilot and driver broadcasting on the same 27MHz frequency would cause interference and could cause a crash. 50MHz channels can be used for R/C, but require the user to attain a Technician-class Amateur Radio License from the FCC.
A common wireless remote control system based on standard APIs of robots is presented to enable a stable multi-robot transportation in distributed life science laboratories. This system consists of multi-robot board control centers (PCs), a remote server control center (PC), a wireless communication network and an infrared radio navigation module with ceiling passive landmarks. To let this system expand conveniently, the two-level Client/Server architecture is adopted, and a standard IEEE 802.11g wireless communication with TCP/IP protocol is utilized. An inside architecture is employed for signal sampling and controlling between robot board PCs and the robot’s hardware modules. An additional outside architecture is designed for higher remote commands between robot board PCs and remote server control PC. Two experiments in this study show that the simple ceiling landmark method is suitable for the robot indoor navigation with low costs, and this kind of remote control system can work effectively in large and distributed laboratory.
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techkhabarsite 
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