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Japanese scientists develop ‘98 percent accurate’ robotic grasping system

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Researchers from Shibaura Institute of Technology, Japan, have developed a novel 6D (six degrees-of-freedom) pose dataset designed to improve robotic grasping accuracy and adaptability in industrial settings. They used an Intel RealSense depth D435 camera in their experiments. 

The dataset, which integrates RGB and depth images, demonstrates significant potential to enhance the precision of robots performing pick-and-place tasks in dynamic environments.

Accurate object pose estimation refers to the ability of a robot to determine both the position and orientation of an object. It is essential for robotics, especially in pick-and-place tasks, which are crucial in industries such as manufacturing and logistics. [Read more…] about Japanese scientists develop ‘98 percent accurate’ robotic grasping system

AgiBot launches ‘by far the largest dataset’ for humanoid robots

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AgiBot, a robotics startup specialising in developing humanoid robots, has launched what it describes as “by far the largest humanoid manipulation dataset” in the world. 

Named “AgiBot World”, it is said by AgiBot to be the first large-scale robotic learning dataset specifically designed to advance multi-purpose robotic policies.

This comprehensive ecosystem includes not only the dataset but also foundational models, standardized benchmarks, and a collaborative framework aimed at democratizing access to high-quality robotic data. [Read more…] about AgiBot launches ‘by far the largest dataset’ for humanoid robots

Motional expands nuScenes datasets for autonomous driving

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Motional, a startup developing driverless vehicle technology, has expanded nuScenes, the dataset that teaches autonomous vehicles how to safely engage with ever-changing road environments – nuScenes now includes nuScenes-lidarseg and nuImages.

nuScenes, created in March 2019, was the first publicly available dataset of its kind, and pioneered an industry-wide culture of safety-focused data-sharing and collaboration.

It launched as a collection of 1,000 urban “street-scenes” in Boston and Singapore. The scenes, composed of millions of photos and data-points collected from the vehicles’ full sensor suites, were then meticulously hand-annotated, and used to inform and advance machine learning models to build the safest possible self-driving vehicles. [Read more…] about Motional expands nuScenes datasets for autonomous driving

FLIR releases European thermal imaging dataset for automotive driver assistance development

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FLIR Systems has made available its first European thermal imaging regional dataset and the third in a series of thermal imaging datasets for machine vision testing.

The company says the dataset is designed to help researchers, developers and auto manufacturers enhance and accelerate work on safety, advanced driver assistance systems (ADAS), automatic emergency braking (AEB) and autonomous vehicle systems.

The dataset features thousands of annotated thermal images of daytime, nighttime and various weather scenarios from six cities across Europe. [Read more…] about FLIR releases European thermal imaging dataset for automotive driver assistance development

Want to know how safe your warehouse job is? There’s an app for that

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In 2017 there were nearly 350,000 incidents of workers taking sick leave due to injuries affecting muscles, nerves, ligaments or tendons – like carpal tunnel syndrome – according to the US Bureau of Labor Statistics.

Among the workers with the highest number of incidents: people who work in factories and warehouses.

Musculoskeletal disorders happen at work when people use awkward postures or perform repeated tasks. These behaviors generate strain on the body over time. So it’s important to point out and minimize risky behaviors to keep workers healthy on the job. [Read more…] about Want to know how safe your warehouse job is? There’s an app for that