Robot Picking
Assembly Line
Pickle Robot Messy Trailer Unload Demonstration
3D Vision-Guided Racking of Reflective Sheet Metal Parts
RightHand Robotics Signs Multi-Year Agreement with Staples® to Deploy AI-Powered Picking Robots in Fulfillment Centers
RightHand Robotics, a leader in autonomous AI robotic picking solutions for order fulfillment, announces a multi-year agreement with Staples Inc., America’s leader in workspace products and solutions. The agreement allows Staples to deploy and install the company’s RightPick™ item-handling system to automate operations for higher service levels and Next-Day Delivery to over 98% of the U.S.
Mitsubishi Electric Automation Demo: Multi-Robot Bin Picking
How Delta Robotics Optimize and Streamline Electronics Manufacturing Processes
Delta robots are relatively small robots employed in handling food items for packaging, pharmaceuticals for casing, and electronics for assembly. The robots’ precision and high speed make them ideally suited to these applications. Their parallel kinematics enables this fast and accurate motion while giving them a spiderlike appearance that’s quite different from that of articulated-arm robots. Delta robots are usually (though not always) ceiling mounted to tend moving assembly and packaging lines from above. They have a much smaller working volume than an articulated arm, and very limited ability to access confined spaces. That said, their stiffness and repeatability are assets in high-precision processing of delicate workpieces — including semiconductors being assembled.
Delta robots provide affordable and flexible automation for electronics manufacturing. They often provide higher speed and more flexibility than other robotics and automated pick-and-place machines.
🦾♻️ Robotic deep RL at scale: Sorting waste and recyclables with a fleet of robots
In “Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators”, we discuss how we studied this problem through a recent large-scale experiment, where we deployed a fleet of 23 RL-enabled robots over two years in Google office buildings to sort waste and recycling. Our robotic system combines scalable deep RL from real-world data with bootstrapping from training in simulation and auxiliary object perception inputs to boost generalization, while retaining the benefits of end-to-end training, which we validate with 4,800 evaluation trials across 240 waste station configurations.
🦾 Amazon releases largest dataset for training 'pick and place' robots
In an effort to improve the performance of robots that pick, sort, and pack products in warehouses, Amazon has publicly released the largest dataset of images captured in an industrial product-sorting setting. Where the largest previous dataset of industrial images featured on the order of 100 objects, the Amazon dataset, called ARMBench, features more than 190,000 objects. As such, it could be used to train “pick and place” robots that are better able to generalize to new products and contexts.
The scenario in which the ARMBench images were collected involves a robotic arm that must retrieve a single item from a bin full of items and transfer it to a tray on a conveyor belt. The variety of objects and their configurations and interactions in the context of the robotic system make this a uniquely challenging task.
Covariant Robotic Depalletization | Mixed-SKU Pallets
Bridgestone Unveils Soft-Robot Hand for Package Handling
Amazon’s New Robot Can Handle Most Items in the Everything Store
Sparrow could shift the balance between humans and machines in the company’s warehouses, using machine learning algorithms and a custom gripper. Sparrow is designed to pick out items piled in shelves or bins so they can be packed into orders for shipping to customers. That’s one of the most difficult tasks in warehouse robotics because there are so many different objects, each with different shapes, textures, and malleability, that can be piled up haphazardly. Sparrow takes on that challenge by using machine learning and cameras to identify objects piled in a bin and plan how to grab one using a custom gripper with several suction tubes. Amazon demonstrated Sparrow for the first time today at the company’s robotics manufacturing facility in Massachusetts.
Locator studio
OSARO and Zenni Optical Deploy Precise Robotic Bagging System
Your next eyeglass order could be fulfilled faster and more accurately with robots. OSARO Inc. and Zenni Optical Inc. today announced that they have automated the “last meter” of Zenni’s fulfillment center in Novato, Calif. Three OSARO Robotic Bagging Systems will prepare eyewear orders for shipment to U.S. customers.
The companies claimed that the deployment is the first time in the industry that a robot will work with an automated bagging machine to ensure that a customer’s unique eyeglass order is placed into the correct bag for shipment. OSARO said its vision and grasping technology enables robots to accurately and quickly pick items.
Mujin Intelligent Robotics Powers Mixed SKU Piece Picking Robots At FANCL
OSARO 自動梱包ソリューション
Industry 5.0: Adding the Human Edge to Industry 4.0
The arms of pick and place robots are equipped with end effectors similar to human hands that are specifically designed for picking various types of objects. These may include components that are further used in the manufacturing processes of products.
Pick and place robots have a wide range of capabilities. Depending on specific application requirements, they can be equipped with several types of end effectors. The most common ones include vacuum grippers with suction cups, fingered grippers, clawed grippers, magnetic grippers, or custom grippers. To achieve a high level of flexibility, pick and place robots are often equipped with multiple arms and heads. This helps them approach objects from several angles at any given time.