Articles tagged with Industrial Robots
Researchers at Aston University have created an AI-based training method that enables robots to adapt to real-world conditions without extensive data collection. This breakthrough could significantly accelerate innovation in sustainable manufacturing, recycling, and autonomous industrial systems.
A new system can map soil moisture tree by tree, allowing growers to water specific trees if they're dry. Maintaining the right moisture level is crucial for plant health, as too little water can stress trees, while too much water can deprive roots of oxygen.
IITGN researchers develop a novel control framework for flexible continuum robots, called virtual actuation space (VAS), to improve their precision and scalability. VAS reduces the complexity of controlling multi-section robots by using just two parameters: direction and magnitude.
Researchers at Harvard University have developed a new design method for optimizing rolling contact joints in robots, which can lead to better grippers, assistive devices, and more efficient robotic movement. The optimized joints performed spectacularly, correcting misalignment by 99% in knee-assist devices.
A new robotic design uses vine-like structures to lift and grasp a variety of objects, including humans, with a gentler approach. The robot can snake around obstacles, squeeze through tight spaces, and even secure itself in a closed loop to create a sling.
The University of Leicester, in partnership with TWI Ltd, has secured £560k to develop a robot-mounted arc-welding system for in-space repair and manufacturing. The project aims to overcome the challenges of welding in space by developing a new, space-qualified robotic welding capability.
Researchers at North Carolina State University unveiled Rainbow, a self-driving laboratory that autonomously discovers high-performance quantum dots. The system combines advanced robotics and AI to conduct up to 1,000 experiments per day, accelerating materials discovery.
A new imaging technique developed by MIT researchers leverages reflections from wireless signals like Wi-Fi to create accurate 3D reconstructions of objects blocked from view. This approach achieved 96 percent reconstruction accuracy on everyday objects with complex shapes.
Researchers developed novel haptic devices to enable precise robot control with tactile feedback, reducing collisions and improving user proficiency. The devices integrate digital twin technology and augmented reality for enhanced immersion.
The new robotic gripper, called GRIP-tape, uses a combination of softness and stiffness to grasp fragile fruits and vegetables with precision. With its ability to navigate obstacles and deposit objects into containers, the gripper has shown promising results in lifting large fruits like lemons.
A new study finds that industrial robots can significantly lower CO2 emissions in manufacturing exports. However, a U-shaped relationship is uncovered, where emissions initially drop before plateauing, highlighting the need for careful integration of robotics into manufacturing systems.
Researchers will create versatile and easy-to-integrate robots capable of intelligent grasping, fine motor skills, and hand-eye coordination. The goal is to empower diverse workforces with robotic solutions, improving worker productivity and job opportunities.
Researchers at ETH Zurich developed an autonomous excavator called HEAP to construct a 6-meter-high and 65-meter-long dry-stone wall. The excavator uses sensors, machine vision, and algorithms to place stones in the desired location, achieving a high level of precision and speed.
University of Missouri engineers are working on a collaborative human-robot order picking system to speed up the online delivery process. The proposed model aims to optimize key decisions in warehouse operations, allowing robots to navigate efficiently and collaborate with humans to increase efficiency.
Researchers have developed a new miniature robot called Joey that can explore real pipe networks completely on its own, weighing just 70g. The robots are small enough to fit in the palm of your hand and are equipped with energy-efficient sensors to navigate through narrow sections and obstacles.
A new AI system uses artificial neural networks to recognize objects more accurately and stably, despite changing visual inputs. The system mimics human eye movements to improve machine vision capabilities, reducing errors in self-driving cars and other applications.