Hackaday Links: October 29, 2023

October 29, 2023 by Dan Maloney 22 Comments

“As California goes, so goes the nation.” That adage has been true on and off for the last 100 years or so, and it’s true again now that GM’s Cruise self-driving car unit has halted operations across the United States, just a couple of days after California’s DMV suspended its license to conduct driverless tests on state roadways. The nationwide shutdown of testing was undertaken voluntarily by the company and takes their sore beset self-driving taxi fleet off the road in Phoenix, Houston, Austin, Dallas, and Miami, in addition to the California ban, which seemed to be mainly happening in San Francisco. Cruise’s fleet has suffered all manner of indignities over the last few months, from vandalism to “coning” pranks to even being used as rolling hookup spots, and that’s not to mention all the trouble they caused by brigading to the same address or losing games of chicken with a semi and a firetruck. We’re not sure what to make of all this; despite our somewhat snarky commentary on the company’s woes, we take little pleasure in this development other than to the degree it probably increases roadway safety in the former test cities. We really do want to see self-driving cars succeed, at least for certain use cases, but it seems like this is a case of too much, too soon for the technology we currently have at our disposal.

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Full Self-Driving, On A Budget

October 17, 2023 by Bryan Cockfield 35 Comments

Self-driving is currently the Holy Grail in the automotive world, with a number of companies racing to build general-purpose autonomous vehicles that can get from point A to point B with no user input. While no one has brought one to market yet, at least one has promised this feature and had customers pay for it, but continually moved the goalposts for delivery due to how challenging this problem turns out to be. But it doesn’t need to be that hard or expensive to solve, at least in some situations.

The situation in question is driving on a single stretch of highway, and only focuses on steering, so it doesn’t handle the accelerator or brake pedal input. The highway is driven normally, using a webcam to take images of the route and an Arduino to capture data about the steering angle. The idea here is that with enough training the Arduino could eventually steer the car. But first some math needs to happen on the training data since the steering wheel is almost always not turning the car, so the Arduino knows that actual steering events aren’t just statistical anomalies. After the training, the system does a surprisingly good job at “driving” based on this data, and does it on a budget not much larger than laptop, microcontroller, and webcam.

Admittedly, this project was a proof-of-concept to investigate machine learning, neural networks, and other statistical algorithms used in these sorts of systems, and doesn’t actually drive any cars on any roadways. Even the creator says he wouldn’t trust it himself, but that he was pleasantly surprised by the results of such a simple system. It could also be expanded out to handle brake and accelerator pedals with separate neural networks as well. It’s not our first budget-friendly self-driving system, either. This one makes it happen with the enormous computing resources of a single Android smartphone.

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Autonomous Wheelchair Lets Jetson Do The Driving

October 4, 2023 by Tom Nardi 8 Comments

Compared to their manual counterparts, electric wheelchairs are far less demanding to operate, as the user doesn’t need to have upper body strength normally required to turn the wheels. But even a motorized wheelchair needs some kind of input from the user to control it, which still may pose a considerable challenge depending on the individual’s specific abilities.

Hoping to improve on the situation, [Kabilan KB] has developed a self-driving electric wheelchair that can navigate around obstacles by feeding the output of an Intel RealSense Depth Camera and LiDAR module into a Jetson Nano Developer Kit running OpenCV. To control the actual motors, the Jetson is connected to an Arduino which in turn is wired into a common L298N motor driver board.

As [Kabilan] explains on the NVIDIA Blog, he specifically chose off-the-shelf components and the most affordable electric wheelchair he could find to bring the total cost of the project as low as possible. An undergraduate from the Karunya Institute of Technology and Sciences in Coimbatore, India, he notes that this sort of assistive technology is usually only available to more affluent patients. With his cost-saving measures, he hopes to address that imbalance.

While automatic obstacle avoidance would already be a big help for many users, [Kabilan] imagines improved software taking things a step further. For example, a user could simply press a button to indicate which room of the house they want to move to, and the chair could drive itself there automatically. With increasingly powerful single-board computers and the state of open source self-driving technology steadily improving, it’s not hard to imagine a future where this kind of technology is commonplace.

Hackaday Links: October 1, 2023

October 1, 2023 by Dan Maloney 13 Comments

We’ve devoted a fair amount of virtual ink here to casting shade at self-driving vehicles, especially lately with all the robo-taxi fiascos that seem to keep cropping up in cities serving as testbeds. It’s hard not to, especially when an entire fleet of taxis seems to spontaneously congregate at a single point, or all it takes to create gridlock is a couple of traffic cones. We know that these are essentially beta tests whose whole point is to find and fix points of failure before widespread deployment, and that any failure is likely to be very public and very costly. But there’s someone else in the self-driving vehicle business with way, WAY more to lose if something goes wrong but still seems to be nailing it every day. Of course, we’re talking about NASA and the Perseverance rover, which just completed a record drive across Jezero crater on autopilot. The 759-meter jaunt was completely planned by the onboard AutoNav system, which used the rover’s cameras and sensors to pick its way through a boulder-strewn field. Of course, the trip took six sols to complete, which probably would result in negative reviews for a robo-taxi on Earth, and then there’s the whole thing about NASA having a much bigger pot of money to draw from than any start-up could ever dream of. Still, it’d be nice to see some of the tech on Perseverance filtering down to Earth.

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Hackaday Links: September 17, 2023

September 17, 2023 by Dan Maloney 4 Comments

OK, it’s official — everyone hates San Francisco’s self-driving taxi fleet. Or at least so it seems, if this video of someone vandalizing a Cruise robotaxi is an accurate reflection of the public’s sentiment. We’ve been covering the increasingly fraught relationship between Cruise and San Franciscans for a while now — between their cabs crashing into semis and being used for — ahem — non-transportation purposes, then crashing into fire trucks and eventually having their test fleet cut in half by regulators, Cruise really seems to be taking it on the chin.

And now this video, which shows a wannabe Ninja going ham on a Cruise taxi stopped somewhere on the streets of San Francisco. It has to be said that the vandal doesn’t appear to be doing much damage with what looks like a mason’s hammer; except for the windshield and side glass and the driver-side mirror — superfluous for a self-driving car, one would think — the rest of the roof-mounted lidars and cameras seem to get off lightly. Either Cruise’s mechanical engineering is better than their software engineering, or the neo-Luddite lacks the upper body strength to do any serious damage. Or maybe both.

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Teaching A Mini-Tesla To Steer Itself

September 2, 2023 by Dan Maloney 4 Comments

At the risk of stating the obvious, even when you’ve got unlimited resources and access to the best engineering minds, self-driving cars are hard. Building a multi-ton guided missile that can handle the chaotic environment of rush-hour traffic without killing someone is a challenge, to say the least. So if you’re looking to get into the autonomous car game, perhaps it’s best to start small.

If [Austin Blake]’s fun-sized Tesla go-kart looks familiar, it’s probably because we covered the Teskart back when he whipped up this little demon of an EV from a Radio Flyer toy. Adding self-driving to the kart is a natural next step, so [Austin] set off on a journey into machine learning to make it happen. Having settled on behavioral cloning, which trains a model to replicate a behavior by showing it examples of the behavior, he built a bolt-on frame to hold a steering servo made from an electric wheelchair motor, some drive electronics, and a webcam attached to a laptop. Ten or so human-piloted laps around a walking path at a park resulted in a 48,000-image training set, along with the steering wheel angle at each point.

The first go-around wasn’t so great, with the Teskart seemingly bent on going off the track. [Austin] retooled by adding two more webcams, to get a little parallax data and hopefully improve the training data. After a bug fix, the improved model really seemed to do the trick, with the Teskart pretty much keeping in its lane around the track, no matter how fast [Austin] pushed it. Check out the video below to see the Teskart in action.

It’s important to note that this isn’t even close to “Full Self-Driving.” The only thing being controlled is the steering angle; [Austin] is controlling the throttle himself and generally acting as the safety driver should the car veer off course, which it tends to do at one particular junction. But it’s a great first step, and we’re looking forward to further development.

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Hackaday Links: August 20, 2023

August 20, 2023 by Dan Maloney 14 Comments

In some ways, we’ve become a little jaded when it comes to news from Mars, which almost always has to do with the Ingenuity helicopter completing yet another successful flight. And so it was with the report of flight number 54 — almost. It turns out that the previous flight, which was conducted on July 22, suffered a glitch that cut the flight short by forcing an immediate landing. We had either completely missed that in the news, or NASA wasn’t forthcoming with the news, perhaps until they knew more. But the details of the error are interesting and appear related to a glitch that happened 46 flights before, way back in May of 2021, that involves dropped frames from the video coming from the helicopter’s down-facing navigational camera. When this first cropped up back on flight six, it was only a couple of missed frames that nearly crashed the craft, thanks to confusion between the video stream and the inertial data. Flight engineers updated the aircraft’s software to allow for a little more flexibility with dropped frames, which worked perfectly up until the aborted flight 53.

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