Ever look out at a pond, stream, or river, and wonder how deep it is? For large bodies of water that are considered navigable, it’s easy enough to pull up a chart and find out. But what if there’s no public data for the area you’re interested in?
Well, you could spend all day on a little boat taking depth readings and making your own chart, but if you’re anything like [Clay] you could build a solar-powered autonomous robot to do it for you. He’s been working on the boat, which he calls Gumption Trap, for the better part of a year now. If we had to guess, we’d say the experience of designing and building it has ended up being a bit more interesting to him than the actual depth of the water — but that’s fine by us.
The design of the boat is surprisingly economical, as far as marine designs go. Two capped four-inch PVC pipes are used as pontoons, and 3D printed brackets attach those to an aluminum extrusion frame that holds the electronics and solar panel high above the water. This arrangement provides an exceptionally stable platform that would be all but impossible to flip under normal circumstances.
Around the back of the craft, there’s a pair of massive 3D printed thrusters, complete with some remarkably chunky printed propellers. The lack of rudders keeps things simple, with differential thrust between the two motors enough to keep the Gumption pointed in the right direction.
Continue reading “Mapping The Depths With An Autonomous Solar Boat”
One of the most common ways of measuring the speed of a vehicle is by using radar, which typically involves generating radio waves, directing them at a moving vehicle, and measuring the various ways that they return to the device. This is a tried-and-true method, but can be expensive and technically complex. [GeeDub] wanted an easier way of measuring vehicles passing by his home, so he switched to using sonar instead to measure speeds based on the sounds the cars generate themselves.
The method he is using is similar to passive sonar in submarines, which can locate objects underwater based on the sounds they produce. After a false start attempting to measure Doppler shift, he switched to time correlation using two microphones, essentially using stereo audio input to detect subtle differences in arrival times of various sounds to detect the positions of passing vehicles. Doing this fast enough and extrapolating the data gathered, speed information can be calculated. For the data gathering and calculation, [GeeDub] is using a Raspberry Pi to help keep costs down, and some further configuration of the microphones and their power supplies were also needed to ensure quality audio was gathered.
With the system in place in a window, it detected around 9,000 vehicles over a three-day period. The software generates a normal distribution of vehicle speeds for this time, with the distribution centered on around 35 MPH, slightly above the posted speed limit of 30. As long as there’s a clear line of sight to the road using this system it’s just as effective as some other passive systems we’ve seen to measure vehicle speed. Of course, active speed measurement systems are not out of the realm of possibility if you’re willing to spend a little more.
Detecting objects underwater isn’t an easy challenge, especially when things get murky and dark. Radio waves don’t propagate well, so most techniques rely on sound. Sonar is itself farily simple, simply send out a ping and listen for an echo, and that will tell you how far something is. Imaging underwater is significantly harder, because you would additionally need to know where each echo is coming from.
To answer the question of whether it is possible to put together an ultrasonic 3D imager that would cheaply enable anyone to image objects underwater, [Alec Vercruysse] and fellow team members at the Harvey Mudd College set out to create a system that does exactly that. You can read the presentation slides (PDF) or check out the entire project in the GitHub repository.
Continue reading “Supercon 2022: Alec Vercruysse Can See Through Murky Water”
To say that the ocean is a dynamic environment would be a gross understatement, especially when coastlines are involved. Waves crash, tides go in and out, and countless variables make even the usual conditions a guessing game. When [foobarbecue] goes surfing, he tries to take into account all of these things. The best waves at his local beach are directly over an ever-moving sand bar, and their dynamics are affected by depth, another constant variable. [foobarbecue]’s brilliant solution to understanding current conditions? Build a depth finder directly into his surf board!
At the heart of the “surfsonar” is the Ping Sonar Echosounder, a sonar transducer designed for AUV’s and ROV’s. [foobarbecue] embedded the transducer directly into the board. Data is fed to a Raspberry Pi 4b, which displays depth and confidence (a percentage of how sure it is of the measurement) on a 2.13 inch e-Paper Display Hat.
Power is provided by a PiSugar. Charging is done wirelessly, which we’d say is pretty important considering that the whole device is sealed inside a modified surfboard.
While it’s not a low budget build, and there’s yet room for improvement, early reports are positive. Once away from the breaking waves, the device confidently shows the depth. More testing will show if the surfsonar will help [foobarbecue] find that ever-moving sandbar!
Surf hacks are always welcome, we’ve featured the LED Strip Lit Surfboard as well as the Surf Window, which tells its owner if the surf is up. Be sure to let us know about any cool hacks you find when you’re out surfing the ‘net via our Tips Line!
For those who like to muck around in boats, there’s enough to worry about without wondering if you’re going to run aground. And there’s really no way to know that other than to work from charts that show you exactly what lies beneath. But what does one do for places where no such charts exist? Easy — make your own homebrew water depth logger.
Thankfully, gone are the days when an able seaman would manually deploy the sounding line and call out the depth to the bottom. [Neumi]’s sounding rig uses an off-the-shelf sonar depth sounder, one with NMEA, or National Marine Electronic Association, output. Combined with a GPS module and an Arduino with an SD card, the rig can keep track not only of how much water is below it, but exactly where the measurement point is. The whole thing is rigged up to an inflatable dinghy which lets it slowly ply the confines of a small marina, working in and out of the nooks and crannies. A bit of Python and matplotlib stitches that data together into a bathymetric map of the harbor, with pretty fine detail. The chart also takes the tides into account, as the water level varies quite a bit over the four hours it takes to gather all the data. See it in action in the video after the hop.
There’s something cool about revealing the mysteries of the deep, even if they’re not that deep. Want to go a little deeper? We’ve seen that before too.
Continue reading “Homebrew Sounder Maps The Depths In Depth”
When [Ezra Thomas] needed inspiration for his senior design project, he only needed to look as far as his own robot. Built during his high school years from the classic 1979 Frank DaCosta book “How to Build Your Own Working Robot Pet”, [Ezra] had learned the hard way the many limitations and complexities of the wire wrapped 74xx series logic chips surrounding its 8085 processor.
[Ezra] embarked on a quest to recreate the monstrosity in miniature, calling it Pet on a Chip. Using a modern FPGA chip allows the electronics to shrink by an order of magnitude and provides flexibility for future expansion. Implementing an 8 bit CPU on the amply sized FPGA left plenty of room for a VGA GPU, motor controller, serial UART, and more. Programming the CPU is handled by a custom assembler written in Python.
The results? Twelve times less weight, thirteen times less power draw, better performance, and a lot of room for growth. [Ezra] hints at an I2C bus expansion as well as a higher level programming language to make software development less of a hurdle.
The Pet On A Chip is a wonderfully engineered project and we hope that we’ll be seeing more such from [Ezra] as time goes by. Watch his Pet On A Chip in action in the video below the break.
If [Ezra]’s FPGA escapades have you wondering how to get started, you can check out this introduction to FPGA from the 2019 Hackaday Superconference. And if you have your own FPGA creation to share, please let us know via the Tip Line!
Continue reading “Robot Pet Is A Chip Off The Old Logic Block”
All through the cold war, there was a high-stakes game of cat and mouse in play. Nuclear powers like the United States and the Soviet Union would hide submarines armed with nuclear missiles underwater. The other side would try to know where they were so they could be targeted in the event of war. The common wisdom was that the United States had many high tech gadgets to help track enemy submarines, but that the Soviet Union was way behind in this area. This was proven false when a Soviet Victor-class boat followed a US missile submarine for six days. Now, a recently declassified CIA report shows how the Soviets didn’t use sonar at all but developed their own technology.
There is something fascinating about submarines. Like an old sailing ship, submarines are often out of touch with their command bases and the captain is the final authority. Like a space ship, the submarine has to survive in an inimical environment. I guess in all three cases, the crew doesn’t just use technology, they depend on it.
Although the submarine has some non-military uses, there are probably more military subs than any other type. After all, a sub is as close to a cloaking device as any real-life military vehicle has ever had. Before modern technology offered ways to find submarines using sonar or magnetic anomalies, a completely submerged submarine was effectively invisible.
There was a lot of speculation that the Soviet Union lacked sufficient technology to use sonar the way the US did. However, in some cases, they had simply developed different types of detection — many of which the West had discarded as impractical.
Continue reading “Hide Silent, Hide Deep: Submarine Tracking Technologies Of The Cold War”