Tag Archives: describe
#437869 Video Friday: Japan’s Gundam Robot ...
Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. 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!):
ACRA 2020 – December 8-10, 2020 – [Online]
Let us know if you have suggestions for next week, and enjoy today’s videos.
Another BIG step for Japan’s Gundam project.
[ Gundam Factory ]
We present an interactive design system that allows users to create sculpting styles and fabricate clay models using a standard 6-axis robot arm. Given a general mesh as input, the user iteratively selects sub-areas of the mesh through decomposition and embeds the design expression into an initial set of toolpaths by modifying key parameters that affect the visual appearance of the sculpted surface finish. We demonstrate the versatility of our approach by designing and fabricating different sculpting styles over a wide range of clay models.
[ Disney Research ]
China’s Chang’e-5 completed the drilling, sampling and sealing of lunar soil at 04:53 BJT on Wednesday, marking the first automatic sampling on the Moon, the China National Space Administration (CNSA) announced Wednesday.
[ CCTV ]
Red Hat’s been putting together an excellent documentary on Willow Garage and ROS, and all five parts have just been released. We posted Part 1 a little while ago, so here’s Part 2 and Part 3.
Parts 4 and 5 are at the link below!
[ Red Hat ]
Congratulations to ANYbotics on a well-deserved raise!
ANYbotics has origins in the Robotic Systems Lab at ETH Zurich, and ANYmal’s heritage can be traced back at least as far as StarlETH, which we first met at ICRA 2013.
[ ANYbotics ]
Most conventional robots are working with 0.05-0.1mm accuracy. Such accuracy requires high-end components like low-backlash gears, high-resolution encoders, complicated CNC parts, powerful motor drives, etc. Those in combination end up an expensive solution, which is either unaffordable or unnecessary for many applications. As a result, we found the Apicoo Robotics to provide our customers solutions with a much lower cost and higher stability.
[ Apicoo Robotics ]
The Skydio 2 is an incredible drone that can take incredible footage fully autonomously, but it definitely helps if you do incredible things in incredible places.
[ Skydio ]
Jueying is the first domestic sensitive quadruped robot for industry applications and scenarios. It can coordinate (replace) humans to reach any place that can be reached. It has superior environmental adaptability, excellent dynamic balance capabilities and precise Environmental perception capabilities. By carrying functional modules for different application scenarios in the safe load area, the mobile superiority of the quadruped robot can be organically integrated with the commercialization of functional modules, providing smart factories, smart parks, scene display and public safety application solutions.
[ DeepRobotics ]
We have developed semi-autonomous quadruped robot, called LASER-D (Legged-Agile-Smart-Efficient Robot for Disinfection) for performing disinfection in cluttered environments. The robot is equipped with a spray-based disinfection system and leverages the body motion to controlling the spray action without the need for an extra stabilization mechanism. The system includes an image processing capability to verify disinfected regions with high accuracy. This system allows the robot to successfully carry out effective disinfection tasks while safely traversing through cluttered environments, climb stairs/slopes, and navigate on slippery surfaces.
[ USC Viterbi ]
We propose the “multi-vision hand”, in which a number of small high-speed cameras are mounted on the robot hand of a common 7 degrees-of-freedom robot. Also, we propose visual-servoing control by using a multi-vision system that combines the multi-vision hand and external fixed high-speed cameras. The target task was ball catching motion, which requires high-speed operation. In the proposed catching control, the catch position of the ball, which is estimated by the external fixed high-speed cameras, is corrected by the multi-vision hand in real-time.
More details available through IROS on-demand.
[ Namiki Laboratory ]
Shunichi Kurumaya wrote in to share his work on PneuFinger, a pneumatically actuated compliant robotic gripping system.
[ Nakamura Lab ]
Thanks Shunichi!
Motivated by insights into the human teaching process, we introduce a method for incorporating unstructured natural language into imitation learning. At training time, the expert can provide demonstrations along with verbal descriptions in order to describe the underlying intent, e.g., “Go to the large green bowl’’. The training process, then, interrelates the different modalities to encode the correlations between language, perception, and motion. The resulting language-conditioned visuomotor policies can be conditioned at run time on new human commands and instructions, which allows for more fine-grained control over the trained policies while also reducing situational ambiguity.
[ ASU ]
Thanks Heni!
Gita is on sale for the holidays for only $2,000.
[ Gita ]
This video introduces a computational approach for routing thin artificial muscle actuators through hyperelastic soft robots, in order to achieve a desired deformation behavior. Provided with a robot design, and a set of example deformations, we continuously co-optimize the routing of actuators, and their actuation, to approximate example deformations as closely as possible.
[ Disney Research ]
Researchers and mountain rescuers in Switzerland are making huge progress in the field of autonomous drones as the technology becomes more in-demand for global search-and-rescue operations.
[ SWI ]
This short clip of the Ghost Robotics V60 features an interesting, if awkward looking, righting behavior at the end.
[ Ghost Robotics ]
Europe’s Rosalind Franklin ExoMars rover has a younger ’sibling’, ExoMy. The blueprints and software for this mini-version of the full-size Mars explorer are available for free so that anyone can 3D print, assemble and program their own ExoMy.
[ ESA ]
The holiday season is here, and with the added impact of Covid-19 consumer demand is at an all-time high. Berkshire Grey is the partner that today’s leading organizations turn to when it comes to fulfillment automation.
[ Berkshire Grey ]
Until very recently, the vast majority of studies and reports on the use of cargo drones for public health were almost exclusively focused on the technology. The driving interest from was on the range that these drones could travel, how much they could carry and how they worked. Little to no attention was placed on the human side of these projects. Community perception, community engagement, consent and stakeholder feedback were rarely if ever addressed. This webinar presents the findings from a very recent study that finally sheds some light on the human side of drone delivery projects.
[ WeRobotics ] Continue reading
Posted in Human Robots
#437701 Robotics, AI, and Cloud Computing ...
IBM must be brimming with confidence about its new automated system for performing chemical synthesis because Big Blue just had twenty or so journalists demo the complex technology live in a virtual room.
IBM even had one of the journalists choose the molecule for the demo: a molecule in a potential Covid-19 treatment. And then we watched as the system synthesized and tested the molecule and provided its analysis in a PDF document that we all saw in the other journalist’s computer. It all worked; again, that’s confidence.
The complex system is based upon technology IBM started developing three years ago that uses artificial intelligence (AI) to predict chemical reactions. In August 2018, IBM made this service available via the Cloud and dubbed it RXN for Chemistry.
Now, the company has added a new wrinkle to its Cloud-based AI: robotics. This new and improved system is no longer named simply RXN for Chemistry, but RoboRXN for Chemistry.
All of the journalists assembled for this live demo of RoboRXN could watch as the robotic system executed various steps, such as moving the reactor to a small reagent and then moving the solvent to a small reagent. The robotic system carried out the entire set of procedures—completing the synthesis and analysis of the molecule—in eight steps.
Image: IBM Research
IBM RXN helps predict chemical reaction outcomes or design retrosynthesis in seconds.
In regular practice, a user will be able to suggest a combination of molecules they would like to test. The AI will pick up the order and task a robotic system to run the reactions necessary to produce and test the molecule. Users will be provided analyses of how well their molecules performed.
Back in March of this year, Silicon Valley-based startup Strateos demonstrated something similar that they had developed. That system also employed a robotic system to help researchers working from the Cloud create new chemical compounds. However, what distinguishes IBM’s system is its incorporation of a third element: the AI.
The backbone of IBM’s AI model is a machine learning translation method that treats chemistry like language translation. It translates the language of chemistry by converting reactants and reagents to products through the use of Statistical Machine Intelligence and Learning Engine (SMILE) representation to describe chemical entities.
IBM has also leveraged an automatic data driven strategy to ensure the quality of its data. Researchers there used millions of chemical reactions to teach the AI system chemistry, but contained within that data set were errors. So, how did IBM clean this so-called noisy data to eliminate the potential for bad models?
According to Alessandra Toniato, a researcher at IBM Zurichh, the team implemented what they dubbed the “forgetting experiment.”
Toniato explains that, in this approach, they asked the AI model how sure it was that the chemical examples it was given were examples of correct chemistry. When faced with this choice, the AI identified chemistry that it had “never learnt,” “forgotten six times,” or “never forgotten.” Those that were “never forgotten” were examples that were clean, and in this way they were able to clean the data that AI had been presented.
While the AI has always been part of the RXN for Chemistry, the robotics is the newest element. The main benefit that turning over the carrying out of the reactions to a robotic system is expected to yield is to free up chemists from doing the often tedious process of having to design a synthesis from scratch, says Matteo Manica, a research staff member in Cognitive Health Care and Life Sciences at IBM Research Zürich.
“In this demo, you could see how the system is synergistic between a human and AI,” said Manica. “Combine that with the fact that we can run all these processes with a robotic system 24/7 from anywhere in the world, and you can see how it will really help up to speed up the whole process.”
There appear to be two business models that IBM is pursuing with its latest technology. One is to deploy the entire system on the premises of a company. The other is to offer licenses to private Cloud installations.
Photo: Michael Buholzer
Teodoro Laino of IBM Research Europe.
“From a business perspective you can think of having a system like we demonstrated being replicated on the premise within companies or research groups that would like to have the technology available at their disposal,” says Teodoro Laino, distinguished RSM, manager at IBM Research Europe. “On the other hand, we are also pushing at bringing the entire system to a service level.”
Just as IBM is brimming with confidence about its new technology, the company also has grand aspirations for it.
Laino adds: “Our aim is to provide chemical services across the world, a sort of Amazon of chemistry, where instead of looking for chemistry already in stock, you are asking for chemistry on demand.”
< Back to IEEE COVID-19 Resources Continue reading
Posted in Human Robots