This Robot Goes Through Life Sideways

We humans walk funny. Pivoting one leg forward at the hip creates an offset that puts us off-balance sideways. We have to compensate for this with each step we take. Many robots handle this by instead taking small, calculated steps. Enter NABiRoS, the Non Anthropomorphic Bipedal Robot System (link to the video below). The ‘Non Anthropomorphic’ means that it doesn’t walk like a human, and yet the ‘Bipedal’ means it still walks on two legs. The difference is that it walks sideways.

NABiRoS leg configuration
NABiRoS leg configuration (from video)

Here’s how the folks from RoMeLa (Robotics & Mechanisms Laboratory) at UCLA did it. Imagine you rotated both your legs 90 degrees such that they were facing in opposite directions. Then you rotate your upper body 90 degrees to face one of your legs. You can now move your legs to walk in the direction you’re facing and there’ll be no more tilting sideways each time you take a step. The joints are also simpler as only a single degree of freedom is needed in each of the knee and hip joints. The ankles and feet are done with a compliant, or an elastic, joint much as you see with a lot of prosthetic legs. As you can see in the video below, in addition to walking, they can do some surprisingly active things such as hopping up and down and what we can only call skipping. In fact, the result is sometimes very human.

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Floating Walking Robot

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.

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A Glimpse Into The Mind Of A Robot Vacuum Cleaner

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.

Looking down on the room and robot
Looking down on the room and robot

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.

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A Robot Arm From The Cupboard

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.

TensorFlow Robot Recognizes Objects

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.

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Simulate Your Robot Before You Build It

[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.