Back at the 2017 Superconference, Hackaday Managing Editor Elliot Williams started his talk about the so-called “Internet of Things” by explaining the only part he doesn’t like about the idea is the Internet… and the things. It’s a statement that most of us would still agree with today. If anything, the situation has gotten worse in the intervening years. Commercial smart gadgets are now cheaper and more plentiful than they’ve ever been, but it seems like precious little has been done to improve their inherent privacy and security issues.
But his talk doesn’t serve to bash the companies producing these devices or even the services that ultimately folded and left their customers with neigh useless gadgets. That’s not his style. The central theme of “Nexus Technologies: Or How I Learned to Love WiFi”is that a smart home can be wonderful thing, assuming it works the way you want it to. Elliot argues that between low-cost modular hardware and open source software, the average hacker has everything they need to build their own self-contained home automation ecosystem. One that’s not only cheaper than what they’re selling at the Big Box electronics store, but also doesn’t invite any of the corporate giants to the party.
Of course, it wasn’t always so. A decade ago it would have been all but impossible, and five years ago it would have been too expensive to be practical. As Elliot details his journey towards a truly personal smart home, he explains the advances in hardware and software that have made it not just possible on the DIY level, but approachable. The real takeaway is that once more people realize how cheap and easy it is to roll your own smart home gadgets, they may end up more than willing to kick Big Brother to the curb and do IoT on their own terms.
This previously unpublished recording somehow slipped between the cracks of the editing room floor but upon recent discovery, it’s still just as relevant today. Take a look at Elliot’s view on Nexus Technologies, then join us after the break for a deeper dive. Make sure to subscribe to Hackaday’s YouTube channel to get in on the 2019 Hackaday Superconference live stream starting Saturday, November 16th.
Chances are pretty good that you’ve got a box or a bin somewhere in your shop with coils of SMD component tapes in it. If you’re lucky, the coils are somewhat contained in their conductive Mylar bags; if you’re more like us, the tapes are flopping around loose in an attempt to seemingly tie themselves together. In either case, these 3D-printed SMD magazines will bring a little order to the chaos, and make board assembly a little bit easier.
When we saw [Robin Reiter]’s build, we thought these would be cassettes for some sort of pick-and-place machine. But while they certainly look like they could be adapted to an automated PnP setup, [Robin]’s main goal was to provide organized storage for loose tapes. Each magazine has a circular reservoir to hold the coiled tape, with an exit slot at the front and a wedge that directs the cover tape in the opposite direction. This removes the cover tape to expose the components, clears it away from the pickup area, and as a bonus, allows the component tape to be advanced just by pulling back on the cover. Each magazine has a spring-loaded latch that clips onto a base that looks a bit like a DIN-rail; the weighted base holds several magazines and makes it easy to set up a manual pick-and-place session. The video below shows all the details.
For certain personality types, this really scratches an itch. We love the modular design, and the organization that these would bring to our shop would really help clean things up a bit. And if [Robin] were ever to take this design to the next level, adding something like this could be useful.
Tesla have always aimed to position themselves as part automaker, part tech company. Their unique offering is that their vehicles feature cutting-edge technology not available from their market rivals. The company has long touted it’s “full self-driving” technology, and regular software updates have progressively unlocked new functionality in their cars over the years.
The latest “V10” update brought a new feature to the fore – known as Smart Summon. Allowing the driver to summon their car remotely from across a car park, this feature promises to be of great help on rainy days and when carrying heavy loads. Of course, the gulf between promises and reality can sometimes be a yawning chasm.
How Does It Work?
Holding the “Come To Me” button summons the vehicle to the user’s location. Releasing the button stops the car immediately.
Smart Summon is activated through the Tesla smartphone app. Users are instructed to check the vehicle’s surroundings and ensure they have line of sight to the vehicle when using the feature. This is combined with a 200 foot (61 m) hard limit, meaning that Smart Summon won’t deliver your car from the back end of a crowded mall carpark. Instead, it’s more suited to smaller parking areas with clear sightlines.
Once activated, the car will back out of its parking space, and begin to crawl towards the user. As the user holds down the button, the car moves, and will stop instantly when let go. Using its suite of sensors to detect pedestrians and other obstacles, the vehicle is touted to be able to navigate the average parking environment and pick up its owners with ease.
No Plan Survives First Contact With The Enemy
With updates rolled out over the air, Tesla owners jumped at the chance to try out this new functionality. Almost immediately, a cavalcade of videos began appearing online of the technology. Many of these show that things rarely work as well in the field as they do in the lab.
As any driver knows, body language and communication are key to navigating a busy parking area. Whether it’s a polite nod, an instructional wave, or simply direct eye contact, humans have become well-rehearsed at self-managing the flow of traffic in parking areas. When several cars are trying to navigate the area at once, a confused human can negotiate with others to take turns to exit the jam. Unfortunately, a driverless car lacks all of these abilities.
This situation proved all too much for the Tesla, and the owner was forced to intervene.
A great example is this drone video of a Model 3 owner attempting a Smart Summon in a small linear carpark. Conditions are close to ideal – a sunny day, with little traffic, and a handful of well-behaved pedestrians. In the first attempt, the hesitation of the vehicle is readily apparent. After backing out of the space, the car simply remains motionless, as two human drivers are also attempting to navigate the area. After backing up further, the Model 3 again begins to inch forward, with seemingly little ability to choose between driving on the left or the right. Spotting the increasing frustration of the other road users, the owner is forced to walk to the car and take over. In a second attempt, the car is again flummoxed by an approaching car, and simply grinds to a halt, unable to continue. Communication between autonomous vehicles and humans is an active topic of research, and likely one that will need to be solved sooner rather than later to truly advance this technology.
Pulling straight out of a wide garage onto an empty driveway is a corner case they haven’t quite mastered yet.
An expensive repair bill, courtesy of Smart Summon.
Other drivers have had worse experiences. One owner had their Tesla drive straight into the wall of their garage, an embarrassing mistake even most learner drivers wouldn’t make. Another had a scary near miss, when the Telsa seemingly failed to understand its lack of right of way. The human operator can be seen to recognise an SUV approaching at speed from the vehicle’s left, but the Tesla fails to yield, only stopping at the very last minute. It’s likely that the Smart Summon software doesn’t have the ability to understand right of way in parking environments, where signage is minimal and it’s largely left up to human intuition to figure out.
This is one reason why the line of sight requirement is key – had the user let go of the button when first noticing the approaching vehicle, the incident would have been avoided entirely. Much like other self-driving technologies, it’s not always clear how much responsibility still lies with the human in the loop, which can have dire results. And more to the point, how much responsibility should the user have, when he or she can’t know what the car is going to decide to do?
More amusingly, an Arizona man was caught chasing down a Tesla Model 3 in Phoenix, seeing the vehicle rolling through the carpark without a driver behind the wheel. While the embarassing incident ended without injury, it goes to show that until familiarity with this technology spreads, there’s a scope for misunderstandings to cause problems.
It’s Not All Bad, Though
Some users have had more luck with the feature. While it’s primarily intended to summon the car to the user’s GPS location, it can also be used to direct the car to a point within a 200 foot radius. In this video, a Tesla can be seen successfully navigating around a sparsely populated carpark, albeit with some trepidation. The vehicle appears to have difficulty initially understanding the structure of the area, first attempting a direct route before properly making its way around the curbed grass area. The progress is more akin to a basic line-following robot than an advanced robotic vehicle. However, it does successfully avoid running down its owner, who attempts walking in front of the moving vehicle to test its collision avoidance abilities. If you value your limbs, probably don’t try this at home.
No, not like that!
Wanting to explore a variety of straightforward and oddball situations, [DirtyTesla] decided to give the tech a rundown himself. The first run in a quiet carpark is successful, albeit with the car weaving, reversing unnecessarily, and ignoring a stop sign. Later runs are more confident, with the car clearly choosing the correct lane to drive in, and stopping to check for cross traffic. Testing on a gravel driveway was also positive, with the car properly recognising the grass boundaries and driving around them. That is, until the fourth attempt, when the car gently runs off the road and comes to a stop in the weeds. Further tests show that dark conditions and heavy rain aren’t a show stopper for the system, but it’s still definitely imperfect in operation.
Reality Check
Fundamentally, there’s plenty of examples out there that suggest this technology isn’t ready for prime-time. Unlike other driver-in-the-loop aids, like parallel parking assists, it appears that users put a lot more confidence in the ability of Smart Summon to detect obstacles on its own, leading to many near misses and collisions.
If all it takes is a user holding a button down to drive a 4000 pound vehicle into a wall, perhaps this isn’t the way to go. It draws parallels to users falling asleep on the highway when using Tesla’s AutoPilot – drivers are putting ultimate trust in a system that is, at best, only capable when used in combination with a human’s careful oversight. But even then, how is the user supposed to know what the car sees? Tesla’s tools seem to have a way of lulling users into a false sense of confidence, only to be betrayed almost instantly to the delight of Youtube viewers around the world.
While it’s impossible to make anything truly foolproof, it would appear that Tesla has a ways to go to get Smart Summon up to scratch. Combine this with the fact that in 90% of videos, it would have been far quicker for an able-bodied driver to simply walk to the vehicle and drive themselves, and it definitely appears to be more of a gimmick than a useful feature. If it can be improved, and limitations such as line-of-sight and distance can be negated, it will quickly become a must-have item on luxury vehicles. That may yet be some years away, however. Watch this space, as it’s unlikely other automakers will rest for long!
The Takata airbag case has become the largest product recall in history, caused over 20 deaths, and cost many billions of dollars. Replacement efforts are still ongoing, and sadly, the body count continues to rise. Against this backdrop, further recalls have been announced affecting another type of Takata airbag.
As these airbags were produced before the switch to ammonium nitrate, they have thus far escaped scrutiny as part of existing recalls. Two recent incidents of airbag misdeployments in Australia led to the recall, causing a death and a serious injury. BMW Australia have advised owners not to drive affected vehicles, and are offering loan or hire cars to affected vehicles. Given the age of the affected vehicles, the company is considering a buyback program in the event that suitable replacement parts cannot be made available.
This development is foreboding, as it suggests yet more cars, originally considered safe, are now at risk of injuring or killing occupants in the event of a crash. It’s not yet clear exactly which makes are effected by this recall, but expect the numbers of vehicles to continue to climb.
A makerspace is a great place to use specialty tools that may be too expensive or large to own by oneself, but there are other perks that come with participation in that particular community. For example, all of the skills you’ve gained by using all that fancy equipment may make you employable in some very niche situations. [lukeiamyourfather] from the Dallas Makerspace recently found himself in just that situation, and was asked to image a two-million-year-old fossil.
The fossil was being placed into a CT machine for imaging, but was too thick to properly view. These things tend to be fragile, so he spent some time laser cutting an acrylic stand in order to image the fossil vertically instead of horizontally. Everything that wasn’t fossil had to be non-conductive for the CT machine, so lots of fishing line and foam was used as well. After the imaging was done, he was also asked to 3D print a model for a display in the museum.
This is all going on at the Perot Museum of Nature and Science if you happen to be in the Dallas area. It’s interesting to see these skills put to use out in the wild as well, especially for something as rare and fragile as studying an old fossil. Also, if you’d like to see if your local makerspace measures up to the Dallas makerspace, we featured a tour of it back in 2014, although they have probably made some updates since then.
Over the year or two since the SAO connector specification was published, otherwise known as the Shitty Addon, we’ve seen a huge variety of these daughter boards for our favourite electronic badges. Many of them are works of art, but there’s another subset that’s far less about show and more about clever functionality. [Uri Shaked]’s little SAO is rather unprepossessing to look at, being a small round PCB with only an ATtiny microcontroller, reset button, and solitary LED, but its interest lies not in its looks but its software. It contains a series of CTF puzzles within, and despite its apparent simplicity should contain enough to detain even the hardiest puzzle-solving hackers.
It’s a puzzle of three parts, at the simplest level merely flashing the LED is enough, while the next level involves retrieving a buried string from the firmware and the last requires replacing the string with one of your own. You are only allowed to do so through the SAO connector, but fortunately you do have the benefit of access to the source code to trawl for vulnerabilities. There is a hefty hint that the data sheet for the microcontroller might also be useful.
When it comes to robotic navigation, the usual approach is to go as technically advanced and “smart” as possible. Yet the most successful lifeforms that we know of follow a completely different approach. With limited senses and cognitive abilities, the success of invertebrates like ants and honeybees lie in cooperation in large numbers. A joint team of researchers from TU Delft, University of Liverpool and Radboud University of Nijmegen, decided to try this approach and experimented with a simple navigation technique to allow a swarm of tiny flying robots to explore an unknown environment.
The drones used were of-the-shelf Crazyflie 2.0 micro quadcopters with add-on boards. Sensors consisted of it’s onboard IMU, simple range finding sensors on a Multi-ranger deck for obstacle detection, and a down pointing optical flow sensor, on a Flow deck, to keep track of the distance travelled. To navigate, the drones used a “swarm gradient bug algorithm” (SGBA). Each drone in has different preferred direction of travel from takeoff. When an obstacle encountered, it follows the contour of the obstacle, and then continues in the preferred direction once the path is clear. When the battery drops to 60%, it returns to a wireless homing beacon. While this technique might not be the most efficient, it has the major advantage of being “lightweight” enough to implement on a cheap microcontroller, an STM32F4 in this case. The full research article is available for free, and is a treasure trove of information.
The main application researchers have in mind is for search and rescue. A swarm of drones can explore an unstable or dangerous area, and identify key areas to focus rescue efforts on. This can drastically reduce wasted time and risk to rescue workers. It is always cool to see complex problems being solved with simple solution, and we are keen to see where things go. Check out the video after the break. Continue reading “Tiny Drones Navigate Like Real Bugs”→
