Robotic Canoe Puts Robot Arms To Work

Most robots get around with tracks or wheels, but [Dave] had something different in mind. Sufficiently unbothered by the prospect of mixing electronics and water, [Dave] augmented a canoe with twin, paddle-bearing robotic arms to bring to life a concept he had: the RowboBoat. The result? A canoe that can paddle itself with robotic arms, leaving the operator free to take a deep breath, sit back, and concentrate on not capsizing.

There are a couple of things we really like about this build, one of which is the tidiness of the robotic platform that non-destructively attaches to the canoe itself with custom brackets. A combination of aluminum extrusion and custom brackets, [Dave] designed it with the help of 3D scanning the canoe as a design aid. A canoe, after all, has nary a straight edge nor a right angle in sight. Being able to pull a 3D model into CAD helps immensely in such cases; we have also seen this technique used in refitting a van into an off-grid camper.

The other thing we like is the way that [Dave] drives the arms. The two PiPER robotic arms are driven with ROS, the Robot Operating System on a nearby Jetson Orin Nano SBC. The clever part is the way [Dave] observed that padding and steering a canoe has a lot in common with a differential drive, which is akin to how a tank works. And so, for propulsion, ROS simply treats the paddle-bearing arms as though they were wheels in a differential drive. The arms don’t seem to mind a little water, and the rest of the electronics are protected by a pair of firmly-crossed fingers.

The canoe steers by joystick, but being driven by ROS it could be made autonomous with a little more work. [Dave] has his configuration and code for RowboBoat up on GitHub should anyone wish to take a closer look. Watch it in action in the video, embedded below.

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ManiPylator focusing its laser pointer at a page.

Simulation And Motion Planning For 6DOF Robotic Arm

[Leo Goldstien] recently got in touch to let us know about a fascinating update he posted on the Hackaday.io page for ManiPylator — his 3D printed Six degrees of freedom, or 6DOF robotic arm.

This latest installment gives us a glimpse at what’s involved for command and control of such a device, as what goes into simulation and testing. Much of the requisite mathematics is introduced, along with a long list of links to further reading. The whole solution is based entirely on free and open source (FOSS) software, in fact a giant stack of such software including planning and simulation software on top of glue like MQTT message queues.

The practical exercise for this installment was to have the arm trace out the shape of a heart, given as a mathematical equation expressed in Python code, and it fared quite well. Measurements were taken! Science was done!

We last brought you word about this project in October of 2024. Since then, the project name has changed from “ManiPilator” to “ManiPylator”. Originally the name was a reference to the Raspberry Pi, but now the focus is on the Python programming language. But all the bot’s best friends just call him “Manny”.

If you want to get started with your own 6DOF robotic arm, [Leo] has traced out a path for you to follow. We’d love to hear about what you come up with!

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Printed Robotic Arm Pumps Up With Brushless Motors

[JesseDarr] recently wrote in to tell us about their dynamic Arm for Robitc Mischief (dARM), a mostly 3D printed six degrees of freedom (6DOF) robotic arm that’s designed to be stronger and more capable than what we’ve seen so far from the DIY community.

The secret? Rather than using servos, dARM uses brushless DC (BLDC) motors paired with ODrive S1 controllers. He credits [James Bruton] and [Skyentific] (two names which regular Hackaday readers are likely familiar with) for introducing him to not only the ODrive controllers, but the robotics applications for BLDCs in the first place.

dARM uses eight ODrive controllers on a CAN bus, which ultimately connect up to a Raspberry Pi 4B with a RS485 CAN Hat. The controllers are connected to each other in a daisy chain using basic twisted pair wire, which simplifies the construction and maintenance of the modular arm.

As for the motors themselves, the arm uses three different types depending on where they are located, with three Eaglepower 8308 units for primary actuators, a pair of GB36-2 motors in the forearm, and finally a GM5208-24 for the gripper. Together, [JesseDarr] says the motors and gearboxes are strong enough to lift a 5 pound (2.2 kilogram) payload when extended in a horizontal position.

The project’s documentation includes assembly instructions for the printed parts, a complete Bill of Materials, and guidance on how to get the software environment setup on the Raspberry Pi. It’s not exactly a step-by-step manual, but it looks like there’s more than enough information here for anyone who’s serious about building a dARM for themselves.

If you’d like to start off by putting together something a bit easier, we’ve seen considerably less intimidating robotic arms that you might be interested in.

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Twelve pink tentacles are wrapped around a small, green succulent plant. The leaves seem relatively undisturbed. They are dangling from brass and white plastic pressure fittings attached to a brass circle.

Tentacle Robot Wants To Hold You Gently

Human hands are remarkable pieces of machinery, so it’s no wonder many robots are designed after their creators. The amount of computation required to properly attenuate the grip strength and position of a hand is no joke though, so what if you took a tentacular approach to grabbing things instead?

Inspired by ocean creatures, researchers found that by using a set of pneumatically-controlled tentacles, they could grasp irregular objects reliably and gently without having to faff about with machine learning or oodles of sensors. The tentacles can wrap around the object itself or intertwine with each other to encase parts of an object in its gentle grasp.

The basic component of the device is 12 sections “slender elastomeric filament” which dangle at gauge pressure, but begin to curl as pressure is applied up to 172 kPa. All of the 300 mm long segments run on the same pressure source and are the same size, but adding multiple sized filaments or pressure sources might be useful for certain applications.

We wonder how it would do feeding a fire or loading a LEGO train with candy? We also have covered how to build mechanical tentacles and soft robots, if that’s more your thing.

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Tabletop Handybot Is Handy, And Powered By AI

Decently useful AI has been around for a little while now, and robotic arms have been around much longer. Yet somehow, we don’t have little robot helpers on our desks yet! Thankfully, [Yifei] is working towards that reality with Tabletop Handybot.

What [Yifei] has developed is a robotic arm that accepts voice commands. The robot relies on a Realsense D435 RGB-D camera, which provides color vision with depth information as well. Grounding DINO is used for object detection on the RGB images. Segment Anything and Open3D are used for further processing of the visual and depth data to help the robot understand what it’s looking at. Meanwhile, voice commands are interpreted via OpenAI Whisper, which can feed prompts to ChatGPT for further processing.

[Yifei] demonstrates his robot picking up markers on command, which is a pretty cool demo. With so many modern AI tools available, we’re getting closer to the ideal of robots that can understand and execute on general spoken instructions. This is a great example. We may not be all the way there yet, but perhaps soon. Video after the break.

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Feeding The Fire By Robot

It might seem a little bit counterintuitive, but one of the more carbon-neutral ways of heating one’s home is by burning wood. Since the carbon for the trees came out of the air a geologically insignificant amount of time ago, it’s in effect solar energy with extra steps. And with modern stoves and well-seasoned wood, air pollution is minimized as well. The only downside is needing to feed the fire frequently, which [Anders] solved by building a robot.

[Anders]’ system is centered around a boiler, a system which typically sits in a utility area like a basement and directs its heat to the home via another system, usually hot water. An Arduino Mega controls the system of old boat winches and various motors, with a grabber arm mounted at the end. The arm pinches each log from end to end, allowing it to grab the uneven logs one at a time. The robot also opens the boiler door and closes it again when the log is added, and then the system waits for the correct set of temperature conditions before grabbing another log and adding it. And everything can be monitored remotely with the help of an ESP32.

The robot is reportedly low-maintenance as well, thanks to its low speed and relatively low need for precision. The low speed also makes it fairly safe to work around, which was an important consideration because wood still needs to be added to a series of channels every so often to feed the robot, but this is much less often than one would have to feed logs into a boiler if doing this chore manually. It also improves on other automated wood-burning systems like pellet stoves, since you can skip the pellet-producing middleman step. It also eliminates the need to heat your home by burning fossil fuels, much like this semi-automated wood stove.

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Gesture-Controlled Robot Arm Is A Nifty Educational Build

Traditionally, robot arms have been controlled either by joysticks, buttons, or very carefully programmed routines. However, for [Narongporn Laosrisin’s] homebrew build, they decided to go with gesture control instead.

The MeArm robotic arm is built using laser cut acrylic parts, and can be had in a kit if so desired. It features four servo motors, charged with rotating the arm’s base, pushing the arm forwards and backwards, up and down, and actuating its gripper. The servos are under the command of a micro:bit microcontroller board, which itself receives signals from a second micro:bit which is strapped to the human wishing to control the arm. The second micro:bit detects gestures with its accelerometer, and then sends the relevant commands to the robotic arm’s micro:bit over its built-in radio link. The arm controller then commands the servos to execute the maneuver.

It may be a small robotic arm that doesn’t have the capacity to lift much, but that’s not the point. This project is a great way to teach students how to program microcontrollers, work with sensor inputs, and just generally how to solve engineering puzzles. To that end, it looks like [Narongporn] has a great project on hand for teaching their students. Video after the break.

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