Training A Self-Driving Kart

December 21, 2024 by Bryan Cockfield 1 Comment

There are certain tasks that humans perform every day that are notoriously difficult for computers to figure out. Identifying objects in pictures, for example, was something that seems fairly straightforward but was only done by computers with any semblance of accuracy in the last few years. Even then, it can’t be done without huge amounts of computing resources. Similarly, driving a car is a surprisingly complex task that even companies promising full self-driving vehicles haven’t been able to deliver despite working on the problem for over a decade now. [Austin] demonstrates this difficulty in his latest project, which adds self-driving capabilities to a small go-kart.

[Austin] had been working on this project at the local park but grew tired of packing up all his gear when he wanted to work on his machine-learning algorithms. So he took all the self-driving equipment off of the first kart and incorporated it into a smaller kart with a very small turning radius so he could develop it in his shop.

He laid down some tape on the floor to create the track and then set up the vehicle to learn how to drive by watching and gathering data. The model is trained with a convolutional neural network and this data. The only inputs that the model gets are images from cameras at the front of the kart. At first, it could only change the steering angle, with [Austin] controlling the throttle to prevent crashes. Eventually, he gave it control of the throttle as well, which behaves well except at the fastest speeds.

There were plenty of challenges along the way, especially when compared to the models trained at the park; [Austin] correctly theorized that the cause of the hardship in the park was a lack of contrast at the boundary between the track and any out-of-bounds areas. With a few tweaks to the track, as well as adding some wide-angle lenses to his cameras, he was able to get a model that works fairly well. Getting started on a project like this doesn’t have as high of a barrier to entry as one might imagine, either. Take a look at this comprehensive open-source Python library for self-driving projects. If you want to start smaller, perhaps don’t start with a self-driving kart.

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Hackaday Links: December 15, 2024

December 15, 2024 by Dan Maloney 7 Comments

It looks like we won’t have Cruise to kick around in this space anymore with the news that General Motors is pulling the plug on its woe-beset robotaxi project. Cruise, which GM acquired in 2016, fielded autonomous vehicles in various test markets, but the fleet racked up enough high-profile mishaps (first item) for California regulators to shut down test programs in the state last year. The inevitable layoffs ensued, and GM is now killing off its efforts to build robotaxis to concentrate on incorporating the Cruise technology into its “Super Cruise” suite of driver-assistance features for its full line of cars and trucks. We feel like this might be a tacit admission that surmounting the problems of fully autonomous driving is just too hard a nut to crack profitably with current technology, since Super Cruise uses eye-tracking cameras to make sure the driver is paying attention to the road ahead when automation features are engaged. Basically, GM is admitting there still needs to be meat in the seat, at least for now.

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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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