The Nanoseeker is a compact underwater vehicle in a torpedo-like form factor. [John] designed the Nanoseeker as completely enclosed vehicle: both the thruster and the control fins are all housed within the diameter of the tube. The thruster is ducted with vents on the sides and control fins integrated into the back of the duct assembly.
[John] designed a compact PCB to drive the vehicle, which includes an STM32F4 alongside several sensors. An MPU-9150 provides IMU functionality and two dual motor driver ICs from TI control the throttle and the control fins. [John] also added a Bluetooth radio for remote control functionality. For those who want a closer look, an image of the schematic is up on his blog.
The board is running MicroPython, which is a small Python implementation optimized for microcontrollers. Although [John]’s hardware platform looks great, he’s still getting started on his software. We look forward to seeing how his project develops, as his project is one of the smallest underwater vehicles we’ve seen.
[via Dangerous Prototypes]
[Patrick] has spent a lot of time around ground and aerial based autonomous robots, and over the last few years, he’s noticed a particular need for teams in robotics competitions to break through the ‘sensory bottleneck’ and get good data of the surrounding environment for navigational algorithms. The most well-funded teams in autonomous robotics competitions use LIDARs to scan the environment, but these are astonishingly expensive. With that, [Patrick] set out to create a cheaper solution.
Early this year, [Patrick] learned of an extremely cheap LIDAR sensor. Now [Patrick] is building a robotics distance measurement unit based on this sensor.
Early experiments with mechanically scanned LIDAR sensors centered around the XV-11 LIDAR, the distance sensor found in the Neato Robotics robot vacuum cleaner. [Patrick] became convinced a mechanically scanned LIDAR was the way forward when it came to distance measurement of autonomous robots. Now he’s making his own with an astonishingly inexpensive LIDAR sensor.
The basic idea of [Patrick]’s project is to take the PulsedLight LIDAR-Lite module, add a motor and processing board, and sell a complete unit that will output 360° of distance data to a robot’s main control system. The entire system should cost under $150 when finished; a boon to any students, teams, or hobbyists building an autonomous vehicle.
[Patrick]’s system is based on the PulsedLight LIDAR – a device that’s not shipping yet – but the team behind the LIDAR-Lite says they should have everything ready by the end of the month, all the better, because between these two devices, there’s a lot of cool stuff to be done in the area of autonomous robots.
[Tim] is getting his drone ready for SparkFun’s 2013 Autonomous Vehicle Competition on June 8th. He has a pretty good start, but was having some problems accurately measuring travel distance. The technique he chose for the task was to glue magnets onto the axles of the vehicle and monitor them with a hall effect sensor. Those sensors are finicky and a few problems during testing prompted him to look at a redundant system. Right now he’s experimenting with adding an optical mouse sensor to the autonomous vehicle.
Recently we saw the same concept used, but it was meant for tracking movement of a full-sized automobile. If it can work in that application it should be perfect here since the vehicle is much closer to the ground and will be used in ideal conditions (flat pavement with clear weather). [Tim] cracked open an old HP mouse he had lying around. Inside he found an Avago ADNS-5020 sensor. After grabbing the datasheet he discovered that it’s simply an I2C device. Above you can see the Arduino Leonardo he used for the first tests.
[Tim] coded functions to monitor the chip, including some interesting ones like measuring how in-focus the surface below the sensor is. This brings up a question, is there limit on how fast the vehicle can travel before the sensor fails to report back accurately?
A few guys from Rutgers showed up at Maker Faire with Navi, their vehicle for the 2012 Intelligent Ground Vehicle Competition. Powered by two huge lead acid batteries, Navi features enough high-end hardware to hopefully make it through or around just about any terrain.
Loaded up with a laser range finder, a stereo camera setup, compass, GPS receiver, and a pair of motors capable of pulling 40A, Navi has the all the hardware sensors required to make it around a track with no human intervention. Everything is controlled by a small netbook underneath the control panel, itself loaded up with enough switches and an 8×32 LED matrix to be utterly incomprehensible.
In the videos after the break, the guys from Rutgers show off the systems that went into Navi. There’s also a video showing off Navi’s suspension, an impressive custom-built wishbone setup that will hopefully keep Navi on an even keel throughout the competition.
Also of note: A PDF design report for Navi and Navi’s own blog.
Continue reading “Intelligent autonomous vehicle makes it to Maker Faire”
There have been many self-driving cars made with different levels of success, but probably the most well-known project is the Google car. What you may not have heard of, though is the autonomous Google cart, or golf cart to be exact. The first video after the break explains the motivation behind the cart and the autonomous vehicle project. As with another autonomous vehicle we’ve featured before, they didn’t forget to include an E-stop button (at 1:03)!
In the second video (also after the break) Google’s Sebastian Thrun and Chris Urmson get into more of the details of how Google’s more famous autonomous Prius vehicles work and their travels around different towns in California. A safety driver is still used at this point, but the sensor package includes a roof-mounted 64-beam laser sensor, wheel encoder, radars, and a GPS sensor. With Google’s vast resources as well as their work with Streetview and Google maps, it’ll be interesting to see what comes of this technology. I, for one, welcome our new robotic overlords.
Continue reading “All About the Google Autonomous Vehicle Project”
Although minivans are a staple of moms and dads that drive their kids to school, soccer practice, and the like, this vehicle imagines a time when maybe they won’t even have to. Autonomous cars have been in development for some time, but the video after the break gives a nice close-up view of how this particular vehicle was built and some of the testing that went into it.
Of particular interest was the external luggage pod modified to hold vehicle electronics. Everything is nicely laid out with wire duct to keep it neat. Those in the manufacturing industry might notice several other off-the-shelf components including an area scanner at 0:24 and extruded aluminum framing at 0:45. The apparent “E-stop” button on the passenger side comes from industry as well and may make the rider feel a bit more safe!
If this wasn’t interesting enough, check out this autonomous car by Google that has already driven from San Francisco to Los Angeles!
The AutoNOMOS labs project has found a new way to maneuver its vehicles, your brain. We have looked at a previous version that uses a mostly computerized van under remote control from an iPhone. This one however, named “Brain Driver”, places the operator in the driver’s seat with an EEG strapped to their head.
Going for a more sporty look, the current vehicle is a drive-by-wire Volkswagen Passat wagon filled to the brim with fun toys like LIDAR/ RADAR sensor technology, cameras, and a specialized GPS. The EEG interface is a commercially available Emotiv model, and after a few rounds of training on safe ground, the driver is placed in control of the car.
In one demonstration the car approaches a 4 way intersection, the driver only has to think left or right and the car (intelligently) navigates the turn after coming to a proper stop, and checking for obstacles. In the second demo car and driver are let loose on an unused airport to test responsiveness.
If you like brains, cars, robots, and spinning lasers join us after the break for a video.
Continue reading “Brain Car Interface”