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Jabil to provide manufacturing services for Sarcos

ScienceFather — Sun, 26 Mar 2023 10:22:37 +0000

Sarcos Technology and Robotics Corporation (Sarcos), a company working to design, develop and manufacture advanced robotic systems that redefine human possibilities, is collaborating with Jabil Inc., a manufacturing solutions provider, to expand Sarcos’ production capacity for its robotic systems and sub-systems.

Under the terms of the agreement, Sarcos will utilize Jabil’s broad manufacturing services to produce a variety of leading-edge robotic systems and sub-systems. The company also will be able to leverage Jabil’s global footprint, strategic supplier relationships, and state-of-the-art manufacturing facilities to accelerate volume production while benefiting from advanced supply chain, procurement, and component-sourcing solutions.

“We expect that our relationship with Jabil will advance Sarcos’ manufacturing capabilities tremendously, helping to augment our overall production capacity and enabling us to scale much faster than we could without their support,” Kiva Allgood, president and CEO of the company, said. “We are excited to work with a proven manufacturing services leader that has a long-standing record of success and an established global network of vendors and partners as we begin delivering our robotic systems to our customers.”

Sarcos expects to increase the production of its commercial Robotics technologies throughout 2023, with manufacturing and assembly occurring at a combination of the company’s facilities in Salt Lake City and Pittsburgh, as well as Jabil’s San Jose, California-based production site. Sarcos anticipates that Jabil will primarily produce sub-systems for its commercial products this year, particularly the Guardian XT dexterous robotic system and may also include the Guardian XM intelligent robotic system and Guardian Sea Class Robotic System. Final system assembly is expected to take place at Sarcos facilities.

“Jabil is pleased to provide our value-added manufacturing services, which we are confident will expand Sarcos’ overall production capacity in a highly cost-effective and efficient manner,” Craig Trotter, vice president of the capital equipment business unit at Jabil, said. “Our deep expertise in materials science, mechanical assembly, and human-machine interfaces, along with final assembly and test, will prove pivotal in accelerating world-class production of Sarcos’ industry-leading robotic systems and sub-systems.”

Earlier this month, Sarcos announced that it successfully completed the final validation of its Outdoor Autonomous Manipulation of Photovoltaic Panels (O-AMPP) project.

The post Jabil to provide manufacturing services for Sarcos appeared first on The Robot Report.

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Diagnosis of liver diseases based on artificial intelligence

ScienceFather — Sun, 26 Mar 2023 10:00:00 +0000

doi: 10.1080/02648725.2023.2193057.

Online ahead of print.

Affiliations

Item in Clipboard

Zhe Zhang.

Biotechnol Genet Eng Rev.

2023.

Abstract

Due to a series of problems in the diagnosis of liver disease, the mortality rate of liver disease patients is very high. Therefore, it is necessary for doctors and researchers to find a more effective non-invasive diagnostic method to meet clinical needs. We analyzed data from 416 patients with liver disease and 167 patients without liver disease from northeastern Andhra Pradesh, India. On the basis of considering age, gender and other basic data of patients, this paper uses total bilirubin and other clinical data as parameters to build a diagnostic model. In this paper, the accuracy of artificial intelligence method Random Forest (RF) and Support Vector Machine (SVM) model in the diagnosis of liver patients was compared. The results show that the support vector machine model based on Gaussian kernel function is more excellent in diagnostic accuracy, that is, SVM method is more suitable for the diagnosis of liver diseases.

Keywords:

Liver disease; disease diagnosis; random forest; support vector machine.

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Relativity Space launches first 3D printed rocket

ScienceFather — Sat, 25 Mar 2023 10:07:50 +0000

The first 3D-printed rocket called GLHF from Relativity Space was successfully launched this week. | Credit: Relativity Space

Relativity Space successfully launched a 3D-printed rocket on Wednesday March 24, 2023. The first Terran 1 rocket called “GLHF” (Good Luck Have Fun) lifted off from launch complex 16 at Cape Canaveral. The Terran 1 is the largest 3D-printed object to be launched as a rocket.

After two prior scrubbed launch attempts over the last week, GLHF successfully lifted off from the launch pad, and reached two goals during its brief flight:

Max-Q: the point of greatest aerodynamic pressure on the rocket body
Main engine shut off: the completion of the main engine burn

The rocket failed to reach orbit in what appears to be a secondary rocket engine failure. As of press time, there is no news on the exact failure. Without the secondary engine ignition, the rocket did not have enough power to reach orbit.

Relativity Space uses industrial robots to 3D print the robot body

Relativity Space is innovating through the use of Robotics to 3D print metal items. As shown in the video below, the company uses industrial robot arms to manage the application of welded metal to produce the rocket body and rocket motors. Rocket bodies are currently expensive to manufacture, and 3D printing them promises to reduce costs and reduce weight by creating complex shapes that require less material (by mass) than with current manufacturing methods.

Traditional methods might take 24 months to produce a rocket body, whereas 3D printing can reduce that timeframe to 2 months. Likewise, a 48-month iteration time on a complete rocket assembly can be reduced to 6 months.

The Terran 1 is designed for the future of constellation deployment and resupply. With software-driven design and the use of 3D printing, the payload part of the rocket (in the nose cone) can easily be manufactured to the specs of each individual launch client.

Ultimately, Relativity Space is planning to produce the Terran R reusable robot, further improving the ROI on rocket development as well as the cost per launch. The vision is to create a fleet of reusable rockets to support future missions to the moon, mars and beyond.

The company was founded in 2015 and has raised $1.3B to date. (Crunchbase)

Here’s the live stream of the Terran 1 rocket launch:

The post Relativity Space launches first 3D printed rocket appeared first on The Robot Report.

from The Robot Report – Robotics News, Analysis & Research https://ift.tt/D3g2hpt
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Uncertainty maximization in partially observable domains: A cognitive perspective

ScienceFather — Sat, 25 Mar 2023 10:00:00 +0000

. 2023 Mar 10;162:456-471.

doi: 10.1016/j.neunet.2023.02.044.

Online ahead of print.

Affiliations

¹ Artificial Intelligence Center, Faculty of Electrical Engineering, Czech Technical University in Prague, 12135, Prague, Czech Republic. Electronic address: ramicmir@fel.cvut.cz.
² Artificial Intelligence and Robotics Lab, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan, Italy. Electronic address: andrea.bonarini@polimi.it.

Item in Clipboard

Mirza Ramicic et al.

Neural Netw.

2023.

. 2023 Mar 10;162:456-471.

doi: 10.1016/j.neunet.2023.02.044.

Online ahead of print.

Affiliations

¹ Artificial Intelligence Center, Faculty of Electrical Engineering, Czech Technical University in Prague, 12135, Prague, Czech Republic. Electronic address: ramicmir@fel.cvut.cz.
² Artificial Intelligence and Robotics Lab, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan, Italy. Electronic address: andrea.bonarini@polimi.it.

Item in Clipboard

Abstract

Faced with an ever-increasing complexity of their domains of application, artificial learning agents are now able to scale up in their ability to process an overwhelming amount of data. However, this comes at the cost of encoding and processing an increasing amount of redundant information. This work exploits the possibility of learning systems, applied in partially observable domains, to selectively focus on the specific type of information that is more likely related to the causal interaction among transitioning states. A temporal difference displacement criterion is defined to implement adaptive masking of the observations. It can enable a significant improvement of convergence of temporal difference algorithms applied to partially observable Markov processes, as shown by experiments performed under a variety of machine learning problems, ranging from highly complex visuals as Atari games to simple textbook control problems such as CartPole. The proposed framework can be added to most RL algorithms since it only affects the observation process, selecting the parts more promising to explain the dynamics of the environment and reducing the dimension of the observation space.

Keywords:

Attention mechanisms and development; Cognitive modeling; Entropy; Neural networks for development; Partially observable Markov decision process; Reinforcement learning.

Conflict of interest statement

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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