It’s no secret that we love bizarre robot locomotion, so we are naturally suckers for BALLU (YouTube link, also embedded below) the Bouyancy-Assisted Lightweight Legged Unit. The project started with a simple observation — walking robots are constrained by having to hold themselves up — and removing that constraint make success much easier. Instead of walking, BALLU almost floats and uses what little net weight it does have to push against the ground.
What’s going through the mind of those your autonomous vacuum cleaning robots as they traverse a room? There are different ways to find out such as covering the floor with dirt and seeing what remains afterwards (a less desirable approach) or mounting an LED to the top and taking a long exposure photo. [Saulius] decided to do it by videoing his robot with a fisheye lens from near the ceiling and then making a heatmap of the result. Not being satisfied with just a finished photo, he made a video showing the path taken as the room is being traversed, giving us a glimpse of the algorithm itself.
The robot he used was the Vorwerk VR200 which he’d borrowed for testing. In preparation he cleared the room and strategically placed a few obstacles, some of which he knew the robot wouldn’t get between. He started the camera and let the robot do its thing. The resulting video file was then loaded into some quickly written Python code that uses the OpenCV library to do background subtraction, normalizing, grayscaling, and then heatmapping. The individual frames were then rendered into an animated gif and the video which you can see below.
Building a simple robot arm is a lot more straightforward than it used to be. If you have a laser cutter, or a bit of cash and don’t mind waiting for postage, there are inexpensive kits like the MeArm. If you have a 3D printer, there are any number of 3D-printed designs for you to tackle. What if you need to satisfy your urge to build a robot arm really quickly, and you don’t have a laser cutter or 3D printer? You’ve got a pile of servos from that remote-control project, how can you make the rest?
If you are [roboteurs], you raid the stationery cupboard, and create an arm using rubber bands, paper clips, and binder clips. The binder clips grip the servo arms and hold the whole thing together, the rubber bands provide extra attachment , and the paper clips are bent to form the jaws. It’s not the prettiest or perhaps the most capable of arms, but it undeniably is an arm, and we’d doubt it could be done any more cheaply.
In this particular case, the arm serves as a demonstration piece for [roboteurs]’ Printabots Maker Kit for people without a 3D printer. It uses their controller board, but there is no reason why it could not be used with any other board capable of driving servos.
We’ve covered innumerable robot arms over the years, This one may be the cheapest, but another contender might be this cardboard arm. None of them, however, are as cool as this steam-powered Armatron toy.
Children can do lots of things that robots and computers have trouble with. Climbing stairs, for example, is a tough thing for a robot. Recognizing objects is another area where humans are generally much better than robots. Kids can recognize blocks, shapes, colors, and extrapolate combinations and transformations.
Google’s open-source TensorFlow software can help. It is a machine learning system used in Google’s own speech recognition, search, and other products. It is also used in quite a few non-Google projects. [Lukas Biewald] recently built a robot around some stock pieces (including a Raspberry Pi) and enlisted TensorFlow to allow the robot to recognize objects. You can see a video of the device, below.
[Nurgak] shows how one can use some of the great robotic tools out there to simulate a robot before you even build it. To drive this point home he builds the tutorial off of the easily 3D printable and buildable Robopoly platform.
The robot runs on Robot Operating System at its core. ROS is interesting because of its decentralized and input/output agnostic messaging system. For example, if you leave everything alone but swap out the motor output from actual motors to a simulator, you can see how the robot would respond to any arbitrary input.
[Nurgak] uses another piece of software called V-REP to demonstrate this. V-REP is a simulation suite for robotics and has a few ROS nodes built in. So in order to make a simulated line-following robot, [Nurgak] tells V-REP to send a simulated camera image to the decision making node of the robot in ROS. It then sends the movement messages back to V-REP which drives the pretend robot around.
He runs through a few more examples, proving that it’s entirely possible to become if not a roboticist, at least a really good AI programmer without ever dropping the big money on parts to build a robot.
There’s hardly a day that passes without an Arduino project that spurs the usual salvo of comments. Half the commenters will complain that the project didn’t need an Arduino. The other half will insist that the project would be better served with a much larger computer ranging from an ARM CPU to a Cray.
[Will Moore] has been interested in BEAM robotics — robots with analog hardware instead of microcontollers. His latest project is a sophisticated line follower. You’ve probably seen “bang-bang” line followers that just use a photocell to turn the robot one way or the other. [Will’s] uses a hardware PID (proportional integral derivative) controller. You can see a video of the result below.
[Eric Dirgahayu] wanted to explore underwater with some sensors and cameras. First, he needed a platform to carry them. That led to his Arduino-controlled swimming fish. The fish is made from PVC and some waterproof servos. From the video (see below) it isn’t clear how much control the fish has, but it does swim with an undulating motion like a real fish.