LabVIEW Robotics Documents
With the announcement of LabVIEW Robotics during the Day 1 keynote at NIWeek 2010, the R&D team at NI knew we had to step up and show off our product throughout the conference. Over the past several months, we’ve put our NI LabVIEW Robotics Starter Kit to the test by implementing vision-based obstacle avoidance and adding remotely-operated (teleoperable) functionality. For an audience of NIWeek attendees on the Exhibit Hall floor, however, we had to do more. We came up with a swarm of four Starter Kit robots who didn’t know anything about their surrounding environment and programmed them to work together to discover the physical space, collaborate with each other over WiFi, and collectively build a map.
To whet your appetite, here's a quick illustration of what went on in our demo.
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NIWeek System Diagram
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And here's a quick peek at all of those parts coming together.
Our inspiration was a real-world rescue situation—a battlefield or a car accident in a remote area, for example—where a robot swarm like this one could be deployed to explore the area and then transmit sensor data to human operators or observers who must respond to the situation appropriately. The swarm of robots can operate autonomously or be controlled by remote operators, and out in the open, the robots would use GPS signals for localization.
Why should you care? We’re publishing all of our code for you to draw inspiration from. We used very specific hardware in our demo, which means you won’t just be able to load and run it. However, we think our code is useful because to produce our demo, we had to solve problems very common in the robotics world. Our code and our explanation of it will present some solutions you can draw from when designing your own LabVIEW Robotics applications. We’ll also explain our solutions for the following problems (and more!):
- Establishing wireless communication between four robots, a master robot demo operator machine, driver stations from which you can control the robots, and other components.
- Implementing a non-GPS localization solution that generates information about the position of each robot within the robot arena.
- Enabling each robot to plan paths through the arena to goal position and navigate there autonomously.
Series Contents
Over the next several weeks, we will explore the hardware and software solutions we put together to drive our swarm—everything from the data communication between the robots and a central computer down to the specific distance sensor drivers we used. The specific topics we will cover include:
- Hardware description (see below)
- DaNI: Bigger, Faster, Stronger
- Robot Arena Layout
- Demo Code and File Structure (see below)
- Data Communications
- Localization (simulated GPS)
- Setup
- Acquisition
- Vision processing
- Using a color lookup table
- Driver Station User Interface (Recently added!)
- Camera feed from robot
- Wireless controllers
- Goal finding
- Obstacle Avoidance, Mapping, and Steering
- Range finding (IR Sensor)
- Path Planning
DaNI: Bigger, Faster, Stronger
As we mentioned before, our swarm consisted of four NI Robotics Starter Kit robots, which we’ve affectionately dubbed “DaNI.” Straight from NI, DaNI is a fully assembled robot base with an ultrasonic sensor, encoders, motors, a battery, and an NI Single-Board RIO-based controller, on which LabVIEW Robotics, LabVIEW Real-Time and LabVIEW FPGA Module software runs. You can read more about the stock Starter Kit product in its data sheet and in a system diagram that another Robotics user created. You also can check out the list of parts used on DaNI.
On each of our swarm robots, however, we swapped the ultrasonic sensor for an infrared distance sensor and added an Axis IP camera and a wireless router. You, too, can make these modifications to your DaNI robots using a quick procedure we’ve documented for you – Robot Recipe: Teleoperation Mode for NI Robotics Starter Kit. This was just one of several tasks we performed to produce our demo, but when we finished, DaNI herself was ready for action.
Robot Arena Layout
The environment the robots were to explore and map consisted of a 20 x 20 ft area with walls approximately 2 ft high surrounding the area. In the weeks leading up to NIWeek, we tested the demo in an open area of the office and used cinder blocks as our obstacles. Until we perfected our obstacle avoidance code, we wrapped the blocks in foam to protect the robots. For the actual demo at NIWeek, two large-scale LEGO models representing NI’s largest office building (Mopac C) and its parking garage were the primary obstacles in the arena. Combined, the two buildings consisted of about 14,000 LEGO blocks! We continued using cinder blocks as additional obstacles in the arena.
The image that follows is an overhead view of our robot arena.
Demo Code and File Structure
Now what you’ve been waiting for—click here to download a zip file the code from our NIWeek demo! We used a few different pieces of NI software to write this code, so to open it without tons of VIs missing, you should use a computer with the following software installed:
- LabVIEW 2010
- LabVIEW 2010 Robotics Module
- LabVIEW 2010 Real-Time Module
- LabVIEW 2010 FPGA Module
- NI-RIO drivers
- NI Vision Development Module
- NI Vision Acquisition Software
Once you extract the files to the location where you want to work with the code, you’ll notice that the file structure is relatively flat. To access all of the code from a centralized location, open the following LabVIEW project:
_Main UIs\NIWeek 2010 Robotics Demo.lvproj
This LabVIEW project, shown below, organizes the code similarly to how the documentation in this series of blog posts will be laid out. That is, several virtual folders in the project correspond to forthcoming parts of this series. You can usually use the folder names in the main directory to find the code in which you are interested.
As we mentioned previously, we used very specific hardware in our demo, which means you probably won’t just be able to load the demo and run it. Even so, it’s useful for you to know that when we performed the demo, we ran each of the following VIs (paths as viewed in NIWeek 2010 Robotics Demo.lvproj😞
- My Computer > Data Communications > NI_Robotics_Server UI.lvlib > Server UI.vi
- My Computer > Data Communications > NI_Robotics_Demo Operator UI.lvlib > Demo Operator UI.vi
- My Computer > Localization > NI_Robotics_Localization GPS.lvlib > Localize Main.vi
- My Computer > Driver UI > NI_Robotics_Driver UI.lvlib > Driver Station Main UI.vi
- NI Starter Kit > NI_Robotics_OnBoard Robot Control.lvlib > OnBoard Robot Control.vi
Conclusion.... for Now
Now that we have your attention, we hope you'll come back to the read future installments in this series about how our robotic swarm came together. As we post future installments, we'll gradually explain each of the aspects of our demo until you have the complete story on our robotic swarm glory.
xunangua,
In this demo the robot locations and orientations were determined by an overhead camera. Each robot had a unique visual marker, so images taken by the camera were analyzed to find the markers of each of the robots, then the locations were transmitted to the robotos
In an unconfined outdoor environment you would need to use a GPS sensor to determine robot position. You would probably also want to use a compass to find robot direction, and other sensors like an IMU or LIDAR to improve position measurements.. LabVIEW Robotics includes drivers for these types of sensors (and many others). Do you have a specific application in mind?
-Chris
