Robot Delivery To Your Door

December 29, 2021 by 21 Comments

While online shopping was already very popular in South Korea, it has become even more so as people stay home more during the pandemic. Several robotic delivery services have launched around the city, such as 7-Eleven using the Neubie robot by Neubility, the GS25 convenience store using LG’s CLOi ServeBot, and the Baemin food delivery service using the Delidrive robot.

Love it or hate it, in the dense population of big cities like Seoul the vast majority of people live in apartment complexes. This lends itself well to these robot delivery projects. In fact, many of these pilot projects are only available in one apartment complex, which can consist of ten to twenty 15+ story buildings. Training your robot to navigate the sidewalks, operating the doors, calling the elevators, and buzzing the customer’s home intercom is an easier task when dealing with only one campus.

Some projects are more ambitious, like another Neubility system operating on the Yonsei University Songdo City campus. You can order fried chicken and have it delivered by a Neubie robot, which comes to your address along the sidewalk at a brisk 5 to 6 km/h. There are some issues, however. First of all, government regulations haven’t quite kept up with the technology. These services are basically operating case-by-case, temporary waiver basis. They are not allowed to operate on the streets, and when driving on the sidewalks they have to avoid bumping into people.

We wrote about a prototype RC truck delivery system last year, and covered Amazon drones and Automating Freight Delivery as well. These all show promise, but are not mainstream yet. The vast majority of your orders are still delivered by a person. Will these automated delivery services eventually replace humans? Let us know your thoughts in the comments below.

Telepresence Robot For “Doing The Rounds”

October 3, 2021 by 10 Comments

When you are responsible for maintaining devices at a client’s location, software tools like remote desktop and SSH are great, but sometimes they are not enough. For some problems, you need to get eyes and hands on the device to figure out what’s going on and fix the problem. This is a challenge [Will Donaldson] from EDM Studio is all too familiar with. They develop and maintain interactive museum exhibits all over the world, so they created Omni, a modular telepresence robot for inspection, maintenance, and a variety of other tasks.

The Omni uses a set of three omni-wheels under its base, powered by DC geared motors with encoders, each controlled by a separate motor driver and Arduino Nano. A similar arrangement was used by Mark Rober for his domino art robot. The main controller is a Raspberry Pi 4 running ROS2 (Robot Operating System), which takes inputs from a 360 LIDAR sensor, high-quality camera module, and IMU.

All the components are mounted on a series of plates separated using threaded rods. This arrangement allows for maximum flexibility and space, especially the open-top plate, which has a grid of holes machined in to allow almost anything to be mounted. In this case, a robotic arm is mounted for manipulating the environment. Another neat feature is the charging station connector, consisting of two parallel metal strips on the outside of the robot.

Omni’s mission is very similar to that of Spot, the robotic dog from Boston Dynamics intended, among other things, for Industrial Inspection. What practical purposes would you use Omni for? Let us know in the comments below.

Self-Driving RC Truck Is A Master’s Thesis In Cybernetics And Robotics

October 31, 2020 by 7 Comments

RC cars are a fun pastime, but for many hackers, taking things to the next level involves making the cars drive themselves. For his Masters thesis, [Jon] did just that, building a self-driving robot truck that confidently cruises the floor of his laboratory.

The truck is based on a 1/14th scale Tamiya chassis, and had been fitted out by a prior group with an inductive charging system. On top of this platform, [Jon] added a Jetson TX2 to act as the brains of the system, hooking it up with a Slamtec RPLIDAR scanner to map its surrounding environment. There’s also a Teensy microcontroller onboard which handles synthesizing PWM signals for the radio control hardware that drives the truck, and a Logitech webcam up front for machine vision. The truck is capable of operating in a variety of modes, from full manual operation, to driving based on LIDAR mapping or with an AI controlling the truck based on camera data. The truck is programmed to drive a route including an inductive charging pad so it can keep its power levels up without human intervention.

It’s a great blueprint for a self-driving system, and [Jon]’s thesis goes into great detail on how everything works at the base level (available on this page as a 67 MB PDF). His Code is on Github for the curious. We’ve seen similar projects before too, like this robot that navigates its builder’s house using LIDAR. Video after the break.

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Tiny Robot Beetle Runs On Alcohol

August 26, 2020 by 44 Comments

Batteries have come a long way in the past few centuries, but pale in comparison to hydrocarbon fuels when it comes to energy density. When it comes to packing plenty of juice in a light, compact package, hydrocarbons are the way to go. Recently, researchers have begun to take advantage of this, powering small robots with liquid fuels. Just like Bending Unit 22, aka Bender Bending Rodriguez, this tiny robotic beetle runs on alcohol.

Robeetle can carry up to 2.6 times its own weight, using Nitinol muscle wires to move its legs.

Affectionately named Robeetle, the tiny ‘bot weighs just 88 milligrams, comparable in mass its insectoid contemporaries. It stores methanol in a polyimide film tank, operating for up to 2 hours on a single fill.  As shown in the video, a solely mechanical control system is used to actuate the robot’s legs. In the neutral state, vents in the fuel tank are open, releasing methanol vapor. This passes over nitinol muscle wires coated in a special catalyst which causes the combustion of the methanol, heating the wires. The wires then contract, moving the legs, and closing the vents. When the wire cools, the wires relax, opening the vents and beginning the cycle anew.

While the ‘bot is solely capable of walking in a single direction, it nevertheless shows the possibilities enabled by powering small devices from energy-dense fuels. Waiting for improved battery technologies to develop is such a bore, after all. We look forward to swarms of such ‘bots exploring disaster areas or performing environmental sampling in years to come. The scientific paper outlines the research outcomes in detail.

We love tiny robots at Hackaday; we’ve featured a few in the past, too. Video after the break.

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Dexter Robot Arm Embraces New Manufacturing With First Micro-Factory

March 9, 2020 by 32 Comments

Haddington Dynamics, the company behind the Dexter robot arm that won the 2018 Hackaday Prize, has opened its first microfactory to build robot arms for Australia and Southeast Asia.

You may remember that the combination of Dexter’s makeup and capabilities are what let it stand out among robotics projects. The fully-articulated robot arm can be motion trained; it records how you move the arm and can play back with high precision rather than needing to be taught with code. The high-precision is thanks to a clever encoder makeup that leverages the power of FPGAs to amplify the granularity of its optical encodes. And it embraces advanced manufacturing to combine 3D printed and glue-up parts with mass produced gears, belts,  bearings, and motors.

It’s a versatile robot arm, for a fraction of the cost of what came before it, with immense potential for customization. And did I mention that it’s open source? Continue reading “Dexter Robot Arm Embraces New Manufacturing With First Micro-Factory” →

DARPA Challenge Autonomous Robot Teams To Navigate Unfinished Nuclear Power Plant

March 6, 2020 by 4 Comments

Robots might be finding their footing above ground, but today’s autonomous robots have a difficult time operating underground. DARPA wanted to give the state of the art a push forward, so they are running a Subterranean (SubT) Challenge which just wrapped up its latest round. A great review of this Urban Circuit competition (and some of the teams participating in it) has been published by IEEE Spectrum. This is the second of three underground problem subdomains presented to the participants, six months apart, preparing them for the final event which will combine all three types.

If you missed the livestream or prefer edited highlight videos, they’re all part of DARPAtv’s Subterranean Challenge playlist. Today it starts with a compilation of Urban Circuit highlights and continues to other videos. Including team profiles, video walkthrough of competition courses, actual competition footage, edited recap videos, and the awards ceremony. Half of the playlist are video from the Tunnels Circuit six months ago, so we can compare to see how teams performed and what they’ve learned along the way. Many more lessons were learned in the just-completed Urban Circuit and teams will spend the next six months improving their robots. By then we’ll have the Caves Circuit competition with teams ready to learn new lessons about operating robots underground.

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It Turns Out, Robots Need Tough Love Too

January 8, 2020 by 5 Comments

Showing robots adversarial behavior may be the key to improving their performance, according to a study conducted by the University of Southern California. While a generative adversarial network (GAN), where two neural networks compete in a game, has been demonstrated, this is the first time adversarial human users have been used in a learning effort.

The report was presented at the International Conference on Intelligent Robots and Systems, describing the experiment in which reinforcement learning was used to train robotic systems to create a general purpose system. For most robots, a huge amount of training data is necessary in order to manipulate objects in a human-like way.

A line of research that has been successful in overcoming this problem is having a “human in the loop”, in which a human provides feedback to the system in regards to its abilities. Most algorithms have assumed a cooperating human assistant, but by acting against the system the robot may be more inclined to develop robustness towards real world complexities.

The experiment that was conducted involved a robot attempting to grasp an object in a computer simulation. The human observer observes the simulated grasp and attempts to snatch the object away from the robot if the grasp is successful. This helps the robot discern weak and firm grasps, a crazy idea from the researchers that managed to work. The system trained with the adversary rejected unstable grasps, quickly learning robust grasps for different objects.

Experiments like these can test the assumptions made in the learning task for robotic applications, leading to better stress-tested systems more inclined to work in real-world situations. Take a look at the interview in the video below the break.

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