Robotics projects are always a favorite for hackers. Being able to almost literally bring your project to life evokes a special kind of joy that really drives our wildest imaginations. We imagine this is one of the inspirations for the boom in interactive technologies that are flooding the market these days. Well, [Technovation] had the same thought and decided to build a fully articulated robotic biped.
Each leg has pivot points at the foot, knee, and hip, mimicking the articulation of the human leg. To control the robot’s movements, [Technovation] uses inverse kinematics, a method of calculating join movements rather than explicitly programming them. The user inputs the end coordinates of each foot, as opposed to each individual joint angle, and a special function outputs the joint angles necessary to reach each end coordinate. This part of the software is well commented and worth your time to dig into.
In case you want to change the height of the robot or its stride length, [Technovation] provides a few global constants in the firmware that will automatically adjust the calculations to fit the new robot’s dimensions. Of all the various aspects of this project, the detailed write-up impressed us the most. The robot was designed in Fusion 360 and the parts were 3D printed allowing for maximum design flexibility for the next hacker.
Maybe [Technovation’s] biped will help resurrect the social robot craze. Until then, happy hacking.
Continue reading “Robotic Biped Walks On Inverse Kinematics”
[Umar Qattan] is in tune with his sole and is trying hard to listen to what it has to say.
At a low level, [Umar] is building an insole with an array of force sensors in it. These sensors are affixed to a flexible PCB which is placed in a user’s shoe. A circuit containing a ESP32, IMU, and haptic feedback unit measure the sensors and send data back to a phone or a laptop.
What’s most interesting are the possibilities opened by the data he hopes to collect. The first application he proposes is AR/VR input. The feedback from the user’s feet plus the haptics could provide all sorts of interesting interaction. Another application is dynamically measuring a user’s gait throughout the day and exercise. People could save themselves a lot of knee pain with something like this.
[Umar] also proposes that an insert like this could record a user’s weight throughout the day. Using the data on the weight fluctuation, it should be possible to calculate someone’s metabolism and hydration from this data.
The first thing to notice about [Bijuo]’s cat-sized quadruped robot designs (link is in Korean, Google translation here) is how slim and sleek the legs are. That’s because unlike most legged robots, the limbs themselves don’t contain any motors. Instead, the motors are in the main body, with one driving a half-circle pulley while another moves the limb as a whole. Power is transferred by a cable acting as a tendon and is offset by spring tension in the joints. The result is light, slim legs that lift and move in a remarkable gait.
[Bijuo] credits the Cheetah_Cub project as their original inspiration, and names their own variation Mini Serval, on account of the ears and in keeping with the feline nomenclature. Embedded below are two videos, the first showing leg and gait detail, and the second demonstrating the robot in motion.
Continue reading “Cat Robot’s Secret To Slim Legs? Banish The Motors!”
There are a lot of ways to try to mathematically quantify how healthy a person is. Things like resting pulse rate, blood pressure, and blood oxygenation are all quite simple to measure and can be used to predict various clinical outcomes. However, one you may not have considered is gait velocity, or the speed at which a person walks. It turns out gait velocity is a viable way to predict the onset of a wide variety of conditions, such as congestive heart failure or chronic obtrusive pulmonary disease. It turns out, as people become sick, elderly or infirm, they tend to walk slower – just like the little riflemen in your favourite RTS when their healthbar’s way in the red. But how does one measure this? MIT’s CSAIL has stepped up, with a way to measure walking speed completely wirelessly.
You can read the paper here (PDF). The WiGate device sends out a low-power radio signal, and then measures the reflections to determine a person’s location over time. Alone, however, this is not enough – it’s important to measure the walking speed specifically, to avoid false positives being triggered by a person simply not moving while watching television, for example. Algorithms are used to separate walking activity from the data set, allowing the device to sit in the background, recording walking speed data with no user interaction required whatsoever.
This form of passive monitoring could have great applications in nursing homes, where staff often have a huge number of patients to monitor. It would allow the collection of clinically relevant data without the need for any human intervention; the device could simply alert staff when a patient’s walking pattern is indicative of a bigger problem.
We see some great health research here at Hackaday – like this open source ECG. Video after the break.
Continue reading “Measuring Walking Speed Wirelessly”
You’ve got to walk before you can run, right? Perhaps not, if this bipedal dino-like running robot is any indication.
Officially dubbed a “Planar Elliptical Runner,” the bot is a test platform for bipedal locomotion from the Institute for Human and Machine Cognition. Taking inspiration from the gait of an ostrich — we think it looks more like a T. rex or velociraptor, but same difference — [Jerry Pratt]’s team at IHMC have built something pretty remarkable. Contrary to all the bipedal and quadrupedal robots we’ve seen, like Boston Dynamics’ Big Dog and PETMAN, which all fairly bristle with sensors and actuators, the PER is very stripped down.
A single motor runs the entire drive chain using linkages that will look familiar to anyone who has taken an elliptical trainer apart, and there’s not a computer or sensor on board. The PER keeps its balance by what the team calls “reactive resilience”: torsion springs between the drive sprocket and cranks automatically modulate the power to both the landing leg and the swing leg to confer stability during a run. The video below shows this well if you single-frame it starting at 2:03; note the variable angles of the crank arms as the robot works through its stride.
The treadmill tests are constrained by a couple of plastic sheets, but the next version will run free. It’s not clear yet how directional control will be achieved, not is it obvious how the PER will be able to stop running and keep its balance. But it’s an interesting advance in locomotion and we look forward to seeing what IHMC’s next trick will be.
Continue reading ““Look Ma, No Gyros!”: A Self-Balancing Mechanical Velociraptor”
You may not realize it, but how fast a person walks is an important indicator of overall health. We all instinctively know that we lag noticeably when a cold or the flu hits, but monitoring gait speed can help diagnose a plethora of chronic diseases and conditions. Wearables like Fitbit would be one way to monitor gait speed, but the Computer Science and Artificial Intelligence Lab at MIT thinks there’s a better way: a wireless appliance that measures gait speed passively.
CSAIL’s sensor, dubbed WiTrack (PDF), is a wall-mounted plaque that could be easily concealed as a picture or mirror. It sends out low-power RF signals between about 5- and 7-GHz to perform 3D motion tracking in real time. The WiTrack sensor has a resolution of about 8 cm at those frequencies. With their WiGait algorithms (PDF), the CSAIL team led by [Chen-Yu Hsu] is able to measure not only overall walking speed, but also stride length. That turns out to be critical to predicting the onset of such diseases as Parkinson’s, which has a very characteristic shuffling gait in the early phase of the disease. Mobility impairments from other diseases, like ALS and multiple sclerosis, could also be identified.
WiTrack builds on [Hsu]’s previous work with through-wall RF tracking. It’s nice to see a novel technique coming closer to a useful product, and we’ll be watching to see where this one goes.
Continue reading “Measuring Gait Speed Passively To Diagnose Diseases”
Go into a fancy drug store, and you might just find one of the most amazing sales demonstrations you’ll ever see. Step right up, take your shoes off, and place your feet onto the magical Dr. Scholl’s machine, and you’ll get a customized readout of how your feet touch the ground. As an added bonus, you’ll also get a recommendation for a shoe insert that will make your feet feel better and your shoes fit better.
There is, of course, one problem with this setup. You don’t stand on a footprint measuring device all day. A better solution to the problem of measuring how your feet hit the ground is doing it while you walk. That’s where [chiprobot]’s Alli-Gait-Or Analysis comes in. It’s that Dr. Scholl’s machine tucked into the sole of a shoe. It can be worn while you walk, and it can tell you exactly how your feet work.
[chiprobot]’s robotic shoes consist of a 3D printed insert that holds eighteen piezo transducers per shoe. These are connected to ADCs, which feed into a microcontroller which sends the data out to a computer. That’s simple enough, but making sense of the data is the real problem.
To turn this data into something that could be used for selecting orthotics or simply finding a better shoe, [chiprobot] is plugging this data into Blender and creating some very cool visualizations. It’s good enough to get some serious data off a shoe, and since this Alli-Gait-Or is wearable, the data is much more valid than a machine sitting in a drug store.