Category robots in business

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#335: Autonomous Aircraft by Xwing, with Maxime Gariel

xwing autonomous aircraft

Abate talks to Maxime Gariel, CTO of Xwing about the autonomous flight technology they are developing.


At Xwing, they retrofit traditional aircraft to include multiple sensors such as cameras, lidar, and radar. Using sensor fusion algorithms, they create an exceptionally accurate model of the environment. This model of the environment and advanced path planning and control algorithms allow the plane to autonomously navigate in the airport, take off, fly to a destination, and land, all without a person on board.

Maxime Gariel
Maxime Gariel is the CTO of Xwing, a San Francisco based startup whose mission is to dramatically increase human mobility using fully autonomous aerial vehicles. Xwing is developing a Detect-And-Avoid system for unmanned and remotely piloted vehicles. Maxime is a pilot but he is passionate about making airplanes fly themselves.

Maxime joined Xwing from Rockwell Collins where he was a Principal GNC Engineer. He worked on autonomous aircraft projects including DARPA Gremlins and the AgustaWestland SW4 Solo autonomous helicopter. Before becoming Chief Engineer of the SW4 Solo’s flight control system, he was in charge of the system architecture, redundancy, and safety for the project.

Before Rockwell Collins, he worked on ADS-B based conflict detection as a postdoc at MIT and on autoland systems for airliners at Thales. Maxime earned his MS and PhD in Aerospace Engineering from Georgia Tech and his BS from ISAE-Supaéro (France).

Links

Robot with rapid motor adaptation able to traverse multiple types of terrain

A group of researchers from Carnegie Mellon and UC Berkeley working with a team at Facebook AI has developed a new type of reactive locomotive system for robots. Called rapid motor adaptation, it allows a robot to traverse a variety of terrain types by learning from past experiences. The group has written a paper describing their new technology and how well it worked when tested and have posted it on the arXiv preprint server.

ITRI introduces AI-based high density shuttle rack system

ITRI’s new AI-Based High Density Shuttle Rack System employs AI and existing warehouse technologies | Image credit: ITRI

The Industrial Technology Research Institute (ITRI) in Taiwan has introduced the AI-Based High Density Shuttle Rack System (SRS). This smart storage system, which operates without manpower in thousands of square meters of space, uses Artificial Intelligence to make warehousing decisions.

ITRI’s system is an all-in-one pick, pack and fulfillment system for high volume e-commerce. Current capacities allow up to 1.25 miles of track for robotic shuttles, with vertical lifts for movement up and down as many as 14 floors of storage capacity. Inventory replenishment and picking is enabled by real-time positioning and tracking with low-latency 5G infrastructure.

A proprietary integrated management software system forms the backbone of operations, with big data crunching enabling a constant flow of warehousing decisions driven by changing demand forecasts, including peak volumes produced by holiday seasons or special campaigns.

When new goods enter the warehouse, the system automatically makes volumetric measurements, measuring the weight and size of each item and storing that information in the cloud. It then factors in the popularity of each item, including short term promotions, campaigns, holidays, weather, and other factors, before sending each item to an optimal storage location for maximum efficiency on an ongoing basis. The system also takes into account common combinations (e.g. toothbrush & toothpaste) to further optimize efficiency. It is able to further improve its performance as it learns from order histories as well.

Goods are transported in and out of the SRS in boxes through conveyor belts | Image credit: Ministry of
Economic Affairs (MOEA) Taiwan

Once orders are ready to be shipped, the SRS determines the best path for items to be retrieved from the shelves, and items are timed to arrive simultaneously to the packing area in order to minimize packing time. SRS also assists packing workers by guiding them to each item using light beams and numbers.

The Director of the Service System Technology Center of ITRI -Chen Hui Juan- explains that the SRS leads to improvements in three areas: decision-making accuracy, utilization of space, and speed of shipping.

With AI algorithms and data analysis, as well as information on seasons, weather, holidays, and other factors, the SRS can accurately predict orders that will be arriving in the warehouse, and determine optimal plans for these orders to be stored and shipped.

The combination of optimized placement and shipping for products as well as vertically capable systems allows goods to be delivered 60% faster than traditional warehousing solutions.

While not in widespread use, ITRI’s technology has already been piloted in a Yahoo facility in Taiwan, with HCT Logistics running warehouse operation control and iAmech manufacturing the automation equipment.

The SRS automatically moves goods according to the AI’s decision-making in the Yahoo warehouse | Image credit: Yahoo.com

Plans are in place for several Taiwanese companies to install SRS in various warehouses in Southeast Asia.

Meanwhile, Chen and the rest of the team at ITRI are working to boost performance of the SRS. Dynamic shuttle tracking and positioning technology have been integrated to improve the precision of automation control. Chen reveals that in the future, ITRI plans to integrate robotic arms into the loading process for boxes ready to be shipped out, continue to improve efficiency, and position Taiwan’s smart logistics solutions to compete on a global stage.

Bristol Robotics Lab Virtual Conference 2021 (with videos)

The Bristol Robotics Laboratory (BRL) hosted their first virtual conference last Wednesday, the 30th of June. With over 50 talks, the conference was a gathering of top robotics researchers, business leaders and PhD/post-doctoral students showcasing cutting-edge research. In their four dedicated tracks, speakers covered a wide range of topics such as unmanned aerial vehicles, soft robotics, assistive technologies, human-robot interaction, robot safety & ethics, or swarm robotics, among others. Moreover, there were two panels discussing the future of robotics, and smart automation & startups.

In case you missed the conference, or you would like to re-watch it, BRL has made all the talks available through their dedicated YouTube channel. For your comfort, you’ll find all the videos in the playlist below. To see the details of each track or talk, you can access their programme navigator. Speakers’ email addresses are also available for you to contact them directly.

Would you like to go even deeper? You can now discover where the previous research takes place through their virtual walkthrough. Enjoy!

Better gripping with intelligent picking robots

Production, warehouse, shipping—where goods are produced, stored, sorted or packed, picking also takes place. This means that several individual goods are removed from storage units such as boxes or cartons and reassembled. Researchers at the Karlsruhe Institute of Technology (KIT), together with partners from Germany and Canada, want to make picking robots smarter using distributed AI methods. To do this, they are investigating how to use training data from multiple stations, from multiple plants, or even companies without requiring participants to hand over sensitive company data.

A universal approach to tailoring soft robots

By combining two distinct approaches into an integrated workflow, Singapore University of Technology and Design (SUTD) researchers have developed a novel automated process for designing and fabricating customized soft robots. Their method, published in Advanced Materials Technologies, can be applied to other kinds of soft robots—allowing their mechanical properties to be tailored in an accessible manner.

PHYSFRAME: a system to type check physical frames of reference for robotic systems

To move efficiently and safely within different environments, robotic systems typically monitor both their own movements and their surroundings as they try to navigate safely and avoid nearby obstacles. The measurements they gather generally make sense with respect to a given frame of reference, also known as a coordinate system.
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