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Thursday, 21 August 2014

Raspberry Pi bot from junk

Figure 1
In previous posts I start looked at using ScratchGPIO to control a junkbot  (http://junkbots.blogspot.com/2014/08/junkbot-pi-1-scratchgpio.html) and showed a Pi controlled junkbot briefly in action (http://junkbots.blogspot.co.uk/2014/08/junkbot-raspberry-pi-2-raspberry-pi.html).

In this post I aim to discuss
- Choice of motor controller card
- Provide an example of a drawing junkbot controlled through Scratch and Raspberrry Pi


Choice of interface/Controller card
The card choosen was the 4Tronix PiRoCon card  (http://4tronix.co.uk/store/index.php?rt=product/product&product_id=182). Selected for four reasons
- Price is reasonable (in my opinion).
- Fits straight onto the Pi through the GPIO - no extra cables needed.
- ScratchGPIO has it as an addon so it makes programming it even easier (see http://cymplecy.wordpress.com/2013/10/31/pirocon-from-4tronix/).
- Others are using it for robot projects.

Use it is quite easy plug the board directly on to the GPIO connector of the Raspberry Pi (4tronix provide some advice in section 15 of http://4tronix.co.uk/blog/?p=22 on mounting the board). The only other changes I needed to make because I wasn't powering the motors through the DC input I had to change the jumper settings next to Vin Connector (see http://4tronix.co.uk/blog/?p=41 for layout) to reflect this.



Example
Now for the fun bit get the whole thing to draw (see Figure 1 and the video at the end)!

The junkbot itself is made up of a drinks can, three supports (we used LEGO here but it equally could be straws, sticks), a pen/pencil, and a  motor and broken propeller combination to create an unbalanced motor.

With the Raspberry Pi off, the the motor's wires are connected to the controller card at the connections for MotorA and the battery is also connected. Turn the Pi on and run ScratchGPIO5plus.


Figure 2
Figure 3





Figure 4















The first task is to make the variables AddOn (which will be used to tell the program we are using the PiRoCon card) and MotorA for the motor (see Figure 3).

In Figure 4 the program can be seen, essentially the left and right key spin the junkbot clockwise or anticlockwise by setting the Motor to either +ve or -ve values from 0 to 100. The space bar is used to stop the motor.

As it moves because one of the supports is a pen it draws. See the video below to watch it draw a squiggly line - control is still a challenge.

 
The bot was developed by Hayden Tetley and Scott Turner. Hayden's time was paid  for through the Nuffield Research Placements  Scheme (http://www.nuffieldfoundation.org/nuffield-research-placements).

Related Link

 




If you would like to know more about the Junkbots project contact scott.turner@northampton.ac.uk. The views and opinions is the authors and should not be taken as representing the views of any organisation the author is associated with.

Sunday, 6 April 2014

Free Online Course on Control of Mobile Robots

Free Online Course on Control of Mobile Robots | NooTriX:



This course investigates how to make mobile robots move in effective, safe, and predictable ways. The basic tool for achieving this is "control theory", which deals with the question of how dynamical systems, i.e., systems whose behaviors change over time, can be effectively influenced. In the course, these two domains - controls and robotics - will be interleaved and we will go from the basics of control theory, via robotic examples of increasing complexity - all the way to the research frontier. The course will focus on mobile robots as the target application and problems that will be covered include (1) how to make (teams of) wheeled ground robots avoid collisions while reaching target locations,  (2) how to make aerial, quadrotor robots follow paths in the presence of severe disturbances, and (3) how to locomotive bipedal, humanoid robots.





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Saturday, 29 March 2014

Robotic roll call | The Economist

Daily chart: Robotic roll call | The Economist: "Robotic roll call
Mar 28th 2014, 12:16 by O.M., P.K. and L.P

Automata step, hop, leap, drive and fly from science fiction into reality

ROBOTS come in all shapes and sizes. Their academic makers draw inspiration from elephants, termites and dragonflies alike. Commercial manufacturers seek to find the right form for their function—such as the deep-pan-pizza shape of the floor cleaning Roomba—while dealing with the constraints required by industrial safety. But those designed to explore the possibilities of working with and among people, be it as rescue workers, butlers or care-home helpers, have a tendency to be person shaped, with arms and heads, if not always with legs. The mechanical menagerie below is the full roster of robots featured in our special report here; the complete lineup in a single graphic is here. And see how a robotic cheetah fares in a race among the world's speed record holders here. "



To read more go to:http://www.economist.com/blogs/graphicdetail/2014/03/daily-chart-20?fsrc=scn/tw/te/dc/roboticrollcall



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Opening Cyber Zoo - YouTube

Opening Cyber Zoo - YouTube:







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Video Friday: Squishy Quadrupeds, Fotokite Drone, and Robots From the 1990s - IEEE Spectrum

Video Friday: Squishy Quadrupeds, Fotokite Drone, and Robots From the 1990s - IEEE Spectrum: "Video Friday: Squishy Quadrupeds, Fotokite Drone, and Robots From the 1990s"



For more details go to: http://spectrum.ieee.org/automaton/robotics/robotics-software/video-friday-quadrupeds-fotokite-robots?utm_source=feedburner-robotics&utm_medium=feed&utm_campaign=Feed%3A+IeeeSpectrumRobotics+%28IEEE+Spectrum%3A+Robotics%29





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Friday, 14 March 2014

HyQ Quadruped Robot Is Back With Even More Tricks - IEEE Spectrum





HyQ Quadruped Robot Is Back With Even More Tricks - IEEE Spectrum: "HyQ Quadruped Robot Is Back With Even More Tricks

By Erico Guizzo
Posted 14 Mar 2014 | 0:30 GMT
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Photo: IIT
HyQ, a quadruped robot created by the Italian Institute of Technology, already knew how to walk, trot, and kick. Last year, it learned how to quickly react to avoid falls when stepping on an obstacle. Now HyQ is back with even more tricks."



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ShanghAI Lectures: Tamim Asfour “Robots think with their hands” | Robohub





ShanghAI Lectures: Tamim Asfour “Robots think with their hands” | Robohub: "ShanghAI Lectures: Tamim Asfour “Robots think with their hands”"



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Saturday, 8 March 2014

Onboard quadrocopter failsafe: flight after actuator failure - YouTube

Onboard quadrocopter failsafe: flight after actuator failure - YouTube:





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Why robots will not be smarter than humans by 2029 | Robohub

Why robots will not be smarter than humans by 2029 | Robohub: "Why robots will not be smarter than humans by 2029
Opinions
by Alan Winfield , March 7, 20145 Comments


Statue of Alan Turing. Photo credit: Neil Crosby
In the last few days we’ve seen a spate of headlines like 2029: the year when robots will have the power to outsmart their makers, all occasioned by an Observer interview with Google’s newest director of engineering Ray Kurzweil."



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Sunday, 23 February 2014

Robots link Northampton, Babylon and Baghdad

A paper has recently being published on a collaboration between University of Northampton; University of Babylon; and University of Technology, Baghdad on path-finding using multiple robots in a dynamic environment.





Probabilistic Multi Robot Path Planning in Dynamic Environments: A Comparison between A* and DFS

Safaa H Shwail, Alia Karim and Scott Turner.
International Journal of Computer Applications


Abstract


In this paper, a probabilistic roadmap planner algorithm with the multi robot path planning problem have been proposed by using the A* search algorithm in a dynamic environment. The whole process consists of two phases. In the first phase: Preprocessing phase, the work space is converted into the configuration space, constructing a probabilistic roadmap graph in the free space, and finding the optimal path for each robot using a global planner that avoids the collision with thestatic obstacles. The second phase: Moving phase, moves each robot in a prioritized manner from its starting point to its ending point through a near optimal path with avoiding collision with the moving obstacles and the other robots. A comparison has been done with the depth first algorithm to see the difference. The simulation results shows that choosing A* search algorithm affect positively the speed of the two phases together in comparison to the depth first search algorithm. 




Citation
Safaa H Shwail, Alia Karim and Scott Turner. Article: Probabilistic Multi Robot Path Planning in Dynamic Environments: A Comparison between A* and DFS. International Journal of Computer Applications 82(7):29-34, November 2013. Published by Foundation of Computer Science, New York, USA
DOI:
10.5120/14130-2251


For more details on computing based research in Northampton go to: http://computingnorthampton.blogspot.co.uk/

MIT Robots Adapt and Collaborate Under Real World Conditions

MIT Robots Adapt and Collaborate Under Real World Conditions







"Real world" is a dangerous phrase to talk about when it comes to robots, because robots very seldom find themselves operating alone out there in wild and forlorn places like your living room or office. Autonomy in unstructured environments is an exceptionally difficult problem to tackle, and it gets even harder when you're dealing with multiple robots trying to collaborate on tasks in situations where they might not even be able to talk to each other reliably. MIT has been developing a control program that's able to coordinate multiple robots while dealing with significant uncertainty, and it's quite creative in how it goes about doing it.