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…(ML) models by exposing the neural network to a wide variety of domain parameters in simulation. Isaac Sim can ensure that the synthetic dataset contains sufficient diversity to drive robust model performance, said NVIDIA. This will help the model to generalize when it encounters real-world scenarios. “If we can throw in a lot of data—say, by varying the color or…
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…using a deep learning convolutional neural network fine-tuned for agronomic purposes, it can understand the types and positions of objects facing the machinery, build movement trajectories, and send commands to perform maneuvers. Cognitive Agro Pilot precisely sees the environment around the equipment and works without satellite signals and real-time kinematic (RTK) corrections, the company said. The system can reduce harvesting…
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…compression, image processing, and deep neural network processing to enable cameras to extract valuable data from video streams. Oculii applies AI to radar “For decades, commercial radars have suffered from poor angular resolution and limited FOVs [fields of view] because traditional designs require more antennas for higher resolution,” said Dayton, Ohio-based Oculii. “Additional antennas increase cost, size, and power exponentially,…
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…to the process is a neural network that models the processing of the camera pipeline. It couples this with a differentiable image renderer to enable “inverse rendering,” which computes the 3D scene and materials that would produce an image identical to the input photo. With its Virtual Testing Suite, Aurora runs millions of simulations every day. The company said this…
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…using a deep learning convolutional neural network fine-tuned for agronomic purposes, it can understand the types and positions of objects facing the machinery, build movement trajectories, and send commands to perform maneuvers. From June to October 2020, over 350 New Holland, John Deere and Claas autonomous combines equipped with the Cognitive Agro Pilot system harvested 590,000 metric tons of grain…
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…model training by exposing the neural network to a wide variety of domain parameters in simulation. This helps the model to generalize well when it encounters real world scenarios. In effect, this technique helps teach models what to ignore. Randomizable parameters in NVIDIA Isaac Sim: Color Movement Scale Light Texture Material Mesh Visibility Rotation Train the ML models using NVIDIA…
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…product at AMP Robotics. “Our neural network is built on a data engine that has recognized more than 50 billion containers and packaging types in real-word conditions.” AMP Clarity provides key recycling data Data is seen as key to improving recycling and recovery rates for a circular economy, according to AMP Robotics. As part of the National Recycling Strategy released…
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…we might find that a neural network could learn to better generalize across the full scope of the problem,” said Worker and Gupta. The appearance gap can be further closed with high-fidelity 3D assets and ray tracing or path tracing-based rendering, using physically based materials such as those defined with the Material Definition Language (MDL). Validated sensor models and DR…
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…RIOS’s AI software uses artificial neural network technology that mimics how brains function in determining how to grasp and handle items, Smith explained. “Such techniques are required given the complexity and challenge of piece-picking use cases, which can include high SKU variation, changing environmental and visual conditions, difficult visual properties involved with certain SKUs, fast cycle times, and precision and…
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…learned during training in a neural network that the researchers copied to the real robot. This approach did not require any hand engineering of the robot’s movements — a departure from traditional methods. Most robotic systems use cameras to create a map of the surrounding environment and use that map to plan movements before executing them. The process is slow…
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…we can run a lightweight neural network and train it to process noisy sensor data observed by the moving robot.” “This is in stark contrast with most robots today,” he added. “Typically, a robot arm is mounted on a fixed base and sits on a workbench with a giant computer plugged right into it. Neither the computer nor the sensors…
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…reinforcement learning to train a neural network, which in turn taught the robot to use extrinsic dexterity to grasp objects in its surrounding environment. In this case, the robot manipulates the object in its gripper with the help of the wall or other vertical surface. Previous research on extrinsic dexterity and robotics often designed systems for grasping objects based on…
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…data-capture technologies with sophisticated artificial neural network (ANN) intelligence, said Advanced Navigation. With support from research institutions including the University of Western Australia (UWA), Curtin University, and philanthropic organization Minderoo, Advanced Navigation said it is continuing to establish sustainable technologies to foster the growth of the blue economy, nationally and internationally. “It’s exciting to see Advanced Navigation continue to grow…
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…predefined rules? PIGINet is a neural network that takes in “Plans, Images, Goal, and Initial facts,” then predicts the probability that a task plan can be refined to find feasible motion plans. In simple terms, it employs a transformer encoder, a versatile and state-of-the-art model designed to operate on data sequences. The input sequence, in this case, is information about…
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…robots or humans, but the neural network can also understand doors. If an AMR sees a lift truck, it knows when to stop. Our robot-agnostic fleet manager integrates with WMS and TMS [transportation management systems] if customers have one, and they help us to dispatch orders of higher or lower priority. Our fleet manager collaborates with human pickers and works…
Ultrasonic sensing enhances robotics perception
Cybernetix Ventures’ event kicks off Robotics Tech Week 2026 slate of events
Preview the manufacturing and warehouse components that will be on the…
Preview the manufacturing and warehouse robots and software that will be on…
