Dual crickets mounted on, and powered from the iRobot!

Up to now, determining the orientation of the iRobots required the use of the vision based camera system. This was because each iRobot had only one cricked. The solution is simple: mount an additional one!

Additionally to prevent the rise in battery usage, we decided to evaluate the possibility of powering them using the iRobot battery. Using a simple circuit Kees Slinkman designed for us, the crickets now turn on and off with the iRobots and do not require any batteries anymore!

Pictures of the iRobot with two crickets mounted:

Top view of the iRobot

Front/Top view of the iRobot

Waypoint following and avoiding

Movie resulting from half a year's worth of work.

Two robots following waypoints!

The did it! Anton, Graham, Mark and Marko got a first version of the waypoint following algorithm implemented on the setup. Now extending the view of the camera, so the robots don't have to be nudged gently into it's view!

Ready to expand!

This Monday the long awaited USB to Serial adapters arrived. This means that all crickets can finally be connected to the the computer. This should make the localization software more precise!

Now it is just a matter of installing them on the desktop pc and all the net-books. Luckily this is not much work!

Exciting new assignment for the Bachelor research project!

This assignment is available for Bachelor students of Mechanical Engineering at 3mE, TU Delft. Course code: WBTP303, BSc research project (2011-2012 Q1)

In the field of robotics, small relatively inexpensive mobile robots are becoming more and more common. This is a result of the technological advances and development in relatively inexpensive communication, computation and sensing devices. These small robots, can be used in a variety of applications, ranging from search and rescue to surveillance. Although the objective differs from application to application, in general the underlying assumption is that the robots are capable of moving towards points of interest autonomously. Therefore reliable and computationally cheap algorithms have to be implemented and tested to make this assumed capability a reality.

The aim of the project is to develop such a reliable and computationally cheap algorithm that ensures that a mobile robot (or multiple of them) arrives at desired given locations (way-points) with the right orientation. The algorithm(s) have to be implemented and demonstrated on the real test-bed experiment in the Distributed Robotics Lab at DCSC, where six iRobot Create platforms are available.

Once such algorithm is tested and has shown its reliability, free space is given to creativity to design coordinated way-point following methods with all the available mobile robots. So: Let your mind run free and come up with an exciting way to demonstrate your algorithm!

In short, will you join us, and further the research in this exiting area?

There are some demands and requirements for this project. These are:

1. Select and develop a suitable algorithm for way-point following.
2. Design and implement a Matlab interface that uses the information supplied from the available camera system to drive the mobile robot to the desired location.
3. Test and demonstrate the system.

Also, knowledge of Matlab is required. Knowledge of C++ is a plus but not required.

The Group

From the left: Tim, Andrea, Wessel, Jurjen, Tamas, Magnus. Do you want to be part of the group of the Distributed Robotics Lab? mail us: a.simonetto@tudelft.nl

We are on the Slurf

Read our research ideas on the Slurf at this page

The new location and a swarm of robots

Dear all,
we are setting up the lab in the new, bigger, location. And in the meantime the robots just multiplied :)

have a nice summer

BSc project from the last half year is finally finished. It's focus was to implement and compare control systems to make the robot drive a specified trajectory. The control systems were combinations of 2 state estimators and 4 controllers. The state estimators filter out cricket noise and improve the state update frequentie by using prediction and the odometry data provided by sensors on the robot. The controllers try to control the robot in such a way to follow a timestamped trajectory as accurately as possible by using the data from the state estimator.

The BSc project group implemented a Particle Filter and improved the Unscented Kalman filter that was already present. The implemented controllers are the Linear feedback-, Non Linear feedback-, Dynamic feedback- and a PD controller. Besides these control algorithms a complete new MATLAB framework to test them was build. Finally the different combinations were tested in a simulation environment. The most promissing were tested in the lab with a figure 8 test trajectory. The error with the trajectory was determined using a ceiling mounted vision recognition camera. 

-group 21-713

BSc. Project wrap up

Hi all,

the BSc. Project is finished, and we have very nice results to show! The students designed a new configuration for the iRobot and they compared camera and cricket systems. Below their poster. Things are really moving!

and.. happy new year!

btw, we have the name of the first robot: Druznik. Thanks to the BSc. guys!
-andrea

Some news after some time

Hi all,

lot of things have been done in the last weeks. We do have now an external power supply for the Cricket and .. the Camera is running.
I configured the Camera so that it sends via tcp/ip the data and we have a stream. Thanks to Gabriel and Fankai. I attached here a nice picture.. but more is yet to come.
Good evening to everybody.

Two beacons for one robot

The two beacons localization procedure is in place! more or less.. =)

iRobot remote control via bluetooth

Little robots grow

Dear all, I am here in this late hour session, just to show the amazing job of today (or yesterday), in the hardware shop.. (thanks to Ron). Here is our new bot!


The UKF is getting there, the outlier rejection is in place, now we have to calibrate better the whole procedure.

slaap lekker,
-a

Occam Razor

After two days of work we implemented the Passive mode on the mini-laptop. And here a crazy thing happened.. the estimation procedure worked fine with the range measurements alone, it worked fine with the odometry alone, but, when we tried to put the sensor on the robot it didn't work at all. .. after some unspeakably rude actions, using the Occam razor, we figured out that the source of such a mess was the EM interference of the iRobot on the Cricket clock. We investigated that and we defined as 10 cm the height where the sensor should be placed . We did a basic drawing of the mounting mechanism. We should re-look into the callback stuff now. And we should develop a outliers rejection procedure for the ones still remaining.

Last, a new Cricket batch is arrived!

fijn weekend

iRobot doing an 8-pattern

Callback functions, aka our evil fellows

Today I continued to implement in a nice way the passive mode. I wanted to have a connection over tcp/ip with the Desktop PC, but I figured out that if the sending frequency is too high, the network is not reliable.. I am looking forward for the wifi router.
I figured also out, after two days that.. Matlab is very bad using the callback functions! .. my idea was simple, every sampling time Matlab should implement a controller, I used the timer function; while, whenever a measurement is available Matlab should estimate the state, I used the callback function. Separately they work pretty OK, but.. when I tried to mix them together.. caboom.. Matlab cuts the measurements and it mess up everything. So, either I make the rs working on the Cricket or I change with an easier simple timer.

mmm..

Lab dismissed for the day.

Towards autonomy

Small steps towards autonomy: frustrated by the active mode, I implemented a passive mode on the mini-laptop. So our robots will have complete autonomy.. yeah! So far, I decided for a callback/timer solution for estimation/control, and it is working ok if the robot is going straight. We do have problems if the robot is turning (the filter doesn't catch the motion of the robot, basically because it slips --> to check). Technically, I put the rs as interface between the mini-laptop and the irobot, it works smoothly; I implemented a UKF (which is still to refine and we should put this together with a Multi-lateration for "bad" situations) .. The rs is not working for the Cricket motes, but with the mini-laptop, the serial connection works much better anyway.

Last but not least: cables and connectors have arrived for the external power systems for the Cricket motes. Ron is going to work at this within this week.

have a nice night folks, :P

Problems, problems, problems

Too many problems today. Just to summarize most of the problems that we have been encountering in the past weeks I can say that most of them boil down to the serial port connections. I still have to figure which is the component that fails, either the serial to usb conversion, or the usb hub, or most likely the Matlab interface, but anyway, the ports fail quite often.
Without reliable ports, no reliable timing and localization is possible; too many useful messages are discarded and the whole system will not work.
Today two of the ports fail after less than twenty minutes, so they started to report the upcoming messages without the proper temporal order. Usually you can deal with this closing and reopening the port; unfortunately Matlab crashed during the reopening attempt.

If this was not enough, I don't think the clocks on the sensor nodes are reliable.

We need to have a better strategy for the serial port connections, using something else rather than Matlab and understand which component is the real problem. We should control the beacons, so we could chirp on specified time instants.. therefore we would not need the clock of the sensors.

That's all for the week, have a nice weekend.

New Bachelor Project

A new project has just started. Four bachelor students from Mechanical Engineering are helping me and Tamas to set up the experimental testbed in the new DCSC Robotics Laboratory.

Here three of them and I with one of the robots.

So far we have placed the sensor networks for localization, implemented a routine in Matlab for a simple multilateration and we have started to command one robot. Under, a close look to one of our sensor and to our playground.