Somewhere down the road, you’ll find that your almighty autonomous robot chassis is going to need some sensor feedback. Otherwise, that next small step down the road may end with a blind leap off the coffee table. The first low-cost sensors we might throw at this problem would be sonars or IR rangefinders, but there’s a problem: those sensors only really provide distance data back from the pinpoint view directly ahead of them.
Rest assured, [Jonathan] wrote in to let us know that he’s got you covered. Combining a line laser, camera, and an FPGA, he’s able to detect obstacles that fall within the field of view of the camera and laser.
If you thought writing algorithms in software is tricky, wait till to you try hardware! (We know: division sucks!) [Jonathan] knows no fear though; he’s performing gradient computation on the FPGA directly to detect the laser in the camera image at a wicked 30 frames-per-second. Why roll up your sleeves and take the hardware route, you might ask? If we took a CPU-based approach at the tiny embedded-robot scale, Jonathan estimates a mere 10 frames-per-second. With an FPGA, we’re able to process images about as fast as they’re received.
Jonathan is using the Logi Board, a Kickstarter success we’ve visited in the past, and all of his code is up on the Githubs. If you crack it open, you’ll also find that many of his modules are Wishbone compliant, so developing your own projects with just some of these parts has been made much easier than trying to rip out useful features from a sea of hairy logic.
With computer-vision hardware keeping such a low profile in the hobbyist community, we’re excited to hear more about [Jonathan’s] FPGA-based robotics endeavors.
Continue reading “Robot Vision: Detecting Obstacles with FPGAs and line lasers”
Even though NASA’s Johnson Space Center’s impressive build for the upcoming DARPA Robotics Challenge is one of many entries, it has to be one of the coolest. The gang at IEEE Spectrum got a sneak peak of the robot dubbed “Valkyrie”, which at 1.9m and 125kg boasts 44 degrees of freedom while managing to look like a finished product ready to roll off the shelf. We can expect to see other custom robots at the challenge, but a number of teams will compete with a Boston Dynamics Atlas Robot, which we’ve covered a couple times this year.
A few readers are probably polishing their pitchforks in anticipation of shouting “Not a hack!” but before you do, take a look at the tasks for the robots in this challenge and consider how new this territory is. To that end, the NASA JSC crew seem to have prepared for resolving catastrophes, even if it means throwing together a solution. They’ve designed the limbs for quick removal and even reversibility: the arms are identical and only slight adjustments are required to turn a left arm into a right. Unlike the Atlas, which requires a tether, Valkyrie is battery-operated, and it can run for around an hour before someone needs to crack open the torso and swap in a new one, Iron Man film-style.
The team was also determined to make Valkyrie seem more human, so they added a soft fabric layer to serve as a kind of clothing. According to IEEE Spectrum, it’s even getting custom made footwear from DC Shoes.There are some utilitarian compromises, though: Valkyrie has adopted a shortcut taken by time-constrained animators in many a cartoon, choosing three fingers per hand instead of four. Make sure you watch the video after the break for a closer look.
Continue reading “Robot Battle for the Big Leagues: Valkyrie and the DARPA Challenge”
The Robotic Manta Ray codenamed MantaBot created by the Bio-Inspired Engineering Research Laboratory (BIER Lab) is set to make a splash. The next evolution in underwater Robotics is here. We have seen the likes of robotic fish and Jelly fish now to be added to the school is the MantaBot which has been designed to mimic the unique swimming motion of the Manta Ray,
This biologically inspired under water robot’s has been designed with a primary goal to be autonomous using its onboard electronics to make its own decisions to navigate its watery domain. BIER Lab has received major funding from the Department of Defense (DoD) Multi-disciplinary University Research Initiative (MURI) program. Part of its goal in the long run is to reverse engineer the biological systems of such creatures to the point of creating simulated artificial skin and muscle.
Continue reading “Robotic Manta Ray (Mantabot)”
[Eric] sent in his tutorial on building a Kinect based robot for $500, a low-cost solution to a wife that thinks her husband spends too much on robots.
For the base of his build, [Eric] used an iRobot Create, a derivative of the Roomba that is built exclusive for some hardware hackery. For command and control of the robot, an EEE netbook takes data from the Kinect and sends it to the iRobot over a serial connection.
The build itself is remarkably simple: two pieces of angle aluminum were attached to the iRobot, and a plastic milk crate was installed with zip ties. The Kinect sits on top of the plastic crate and the netbook comfortably fits inside.
A few weeks ago, [Eric] posted a summary of the history and open-source software for the Kinect that covers the development of the Libfreenect driver. [Eric] used this same driver for his robot. Currently, the robot is configured for two modes. The first mode has the robot travel to the furthest point from itself. The second mode instructs the robot to follow the closest thing to itself – walk in front of the robot and it becomes an ankle biter.
There is a limitation of the Kinect that [Eric] is trying to work around. Objects closer than 19 inches to the Kinect appear to be very far away. This caused a lot of wall bumping, but he plans on adding a few ultrasonic sensors to fill the gap in the sensor data. Not bad for a very inexpensive autonomous robot.
[DJ Sures], who built the autonomous Wall-E, is back with another creation. His new autonomous Cookie Monster is certainly an interesting build. He had the cookie monster plush toy already so the first step was to flay the blue beast and insert a skeleton. He used another robot for that. There are two servos for the wheels plus one for each arm and one for the neck. There’s a distance sensor in the mouth. He built a custom board for the PIC18F4685 microcontroller which is running the same 2D mapping code as his previous bot. Check out the video of it in action below. Continue reading “Autonomous Cookie Monster”