Tag Archives: Safety
#439678 Video Friday: Afghan Girls Robotics Team ...
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We'll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!):
DARPA SubT Finals – September 21-23, 2021 – Louisville, KY, USAWeRobot 2021 – September 23-25, 2021 – [Online Event]IROS 2021 – September 27-1, 2021 – [Online Event]ROSCon 2021 – October 20-21, 2021 – [Online Event]Let us know if you have suggestions for next week, and enjoy today's videos.
Five members of an all-girl Afghan robotics team have arrived in Mexico, fleeing an uncertain future at home after the recent collapse of the U.S.-backed government and takeover by the Taliban.
[ Reuters ] via [ FIRST Mexico ]
Thanks, Fan!
As far as autonomous cars are concerned, there's suburban Arizona difficulty, San Francisco difficulty, and then Asia rush hour difficulty. This is a 9:38 long video that is actually worth watching in its entirety because it's a fully autonomous car from AutoX driving through a Shenzhen urban village. Don't miss the astonished pedestrians, the near-miss with a wandering dog, and the comically one-sided human-vehicle interaction on a single lane road.
The AutoX Gen5 system has 50 sensors in total, as well as a vehicle control unit of 2200 TOPS computing power. There are 28 cameras capturing a total of 220 million pixels per second, six high-resolution LiDAR offering 15 million points per second, and 4D RADAR with 0.9-degree resolution encompassing a 360-degree view around the vehicle. Using cameras and LiDAR fusion perception blind spot modules, the Gen5 system covers the entire RoboTaxi body with zero blind spots.[ AutoX ]
Sometimes, robots do nice things for humans.
[ US Soccer ]
Body babbling? Body babbling.
[ CVUT ]
Thanks, Fan!
Matias from the Oxford Robotics Institute writes, “This is a demonstration of our safe visual teach and repeat navigation system running on the ANYmal robot in the Corsham mines/former Cold War bunker in the UK. This is part of some testing we've been doing for the DARPA SubT challenge as part of the Cerberus team.”
[ Oxford Robotics ]
Thanks, Matias!
We built a robotic chess player with a universal robot UR5e, a 2D camera, and a deep-learning neural network to illustrate what we do at the Mechatronics, Automation, and Control System Lab at the University of Washington.
[ MACS Lab ] via [ UW Engineering ]
Thanks, Sarah!
Autonomous inspection of powerlines with quadrotors is challenging. Flights require persistent perception to keep a close look at the lines. We propose a method that uses event cameras to robustly track powerlines. The performance is evaluated in real-world flights along a powerline. The tracker is able to persistently track the powerlines, with a mean lifetime of the line 10x longer than existing approaches.
[ ETHZ ]
I could totally do this, I just choose not to.
[ Flexiv ]
Thanks, Yunfan!
Drone Badminton enables people with low vision to play badminton again using a drone as a ball. This has the potential to diversify the physical activity for people with low vision.
[ Digital Nature Group ]
Even with the batteries installed, the Open Dynamic Robot Initiative's quadruped is still super skinny looking.
[ ODRI ]
At USC's Center for Advanced Manufacturing, we have developed a space for multidisciplinary human-robot interaction. The Baxter robot collaborates with the user to execute their own customizable tie-dye design.
[ USC Viterbi ]
I will never understand the impulse that marketing folks have to add bizarre motor noises to robot videos.
[ DeepRobotics ]
FedEx and Berkshire Grey have teamed up to streamline small package processing.
[ FedEx ]
ABB robot amalyzing COVID tests in a fully automated, unmanned state, back and forth between the stations Assist in the delivery of specimens between points, 24 hours a day, 24 hours a day, test results of 96 specimens can be completed every 60 minutes, processing more than 1,800 specimens per day.
[ ABB ]
Thanks, Fan!
This is, and I quote, “the best and greatest robot death scene of all time.”
[ The Black Hole ]
Thanks, Mark!
Audrow Nash interviews Melonee Wise for the Sense Think Act podcast.
[ Sense Think Act ]
Tom Galluzzo interviews Andrew Thomaz for the Crazy Hard Robots podcast.
[ Crazy Hard Robots ] Continue reading
#439311 Amazon develops new technologies to ...
Teams at the Amazon Robotics and Advanced Technology labs in both Seattle, Washington, and northern Italy have begun diligently testing out new technology they hope will improve safety for employees by carrying out tasks such as transportation of carts, packages and totes through Amazon facilities. Continue reading
#439110 Robotic Exoskeletons Could One Day Walk ...
Engineers, using artificial intelligence and wearable cameras, now aim to help robotic exoskeletons walk by themselves.
Increasingly, researchers around the world are developing lower-body exoskeletons to help people walk. These are essentially walking robots users can strap to their legs to help them move.
One problem with such exoskeletons: They often depend on manual controls to switch from one mode of locomotion to another, such as from sitting to standing, or standing to walking, or walking on the ground to walking up or down stairs. Relying on joysticks or smartphone apps every time you want to switch the way you want to move can prove awkward and mentally taxing, says Brokoslaw Laschowski, a robotics researcher at the University of Waterloo in Canada.
Scientists are working on automated ways to help exoskeletons recognize when to switch locomotion modes — for instance, using sensors attached to legs that can detect bioelectric signals sent from your brain to your muscles telling them to move. However, this approach comes with a number of challenges, such as how how skin conductivity can change as a person’s skin gets sweatier or dries off.
Now several research groups are experimenting with a new approach: fitting exoskeleton users with wearable cameras to provide the machines with vision data that will let them operate autonomously. Artificial intelligence (AI) software can analyze this data to recognize stairs, doors, and other features of the surrounding environment and calculate how best to respond.
Laschowski leads the ExoNet project, the first open-source database of high-resolution wearable camera images of human locomotion scenarios. It holds more than 5.6 million images of indoor and outdoor real-world walking environments. The team used this data to train deep-learning algorithms; their convolutional neural networks can already automatically recognize different walking environments with 73 percent accuracy “despite the large variance in different surfaces and objects sensed by the wearable camera,” Laschowski notes.
According to Laschowski, a potential limitation of their work their reliance on conventional 2-D images, whereas depth cameras could also capture potentially useful distance data. He and his collaborators ultimately chose not to rely on depth cameras for a number of reasons, including the fact that the accuracy of depth measurements typically degrades in outdoor lighting and with increasing distance, he says.
In similar work, researchers in North Carolina had volunteers with cameras either mounted on their eyeglasses or strapped onto their knees walk through a variety of indoor and outdoor settings to capture the kind of image data exoskeletons might use to see the world around them. The aim? “To automate motion,” says Edgar Lobaton an electrical engineering researcher at North Carolina State University. He says they are focusing on how AI software might reduce uncertainty due to factors such as motion blur or overexposed images “to ensure safe operation. We want to ensure that we can really rely on the vision and AI portion before integrating it into the hardware.”
In the future, Laschowski and his colleagues will focus on improving the accuracy of their environmental analysis software with low computational and memory storage requirements, which are important for onboard, real-time operations on robotic exoskeletons. Lobaton and his team also seek to account for uncertainty introduced into their visual systems by movements .
Ultimately, the ExoNet researchers want to explore how AI software can transmit commands to exoskeletons so they can perform tasks such as climbing stairs or avoiding obstacles based on a system’s analysis of a user's current movements and the upcoming terrain. With autonomous cars as inspiration, they are seeking to develop autonomous exoskeletons that can handle the walking task without human input, Laschowski says.
However, Laschowski adds, “User safety is of the utmost importance, especially considering that we're working with individuals with mobility impairments,” resulting perhaps from advanced age or physical disabilities.
“The exoskeleton user will always have the ability to override the system should the classification algorithm or controller make a wrong decision.” Continue reading