Welcome to the next generation of robotics and machinery. LiveDrive LDD is a unique direct drive motor that overcomes almost every limitation of servo geared solutions. No Gearbox. No Downtime. No Contamination.
Bring performance accuracy and reliability, lower total cost of ownership to your robotics and machines with LiveDrive® LDD – our patented direct drive motor eliminates the need for servo gearheads while simplifying robot and machine architecture.
Welcome to the next generation of robotics and machinery. LiveDrive LDD is a unique direct drive motor that overcomes almost every limitation of servo geared solutions. A 50% reduction in length from typical geared motor is possible with Genesis direct drive motors. Choose to simplify machine designs and have a shorter footprint while having high performance, accuracy, and efficiency.
A research team has shown for the first time that reinforcement learning—i.e., a neural network that learns the best action to perform at each moment based on a series of rewards—allows autonomous vehicles and underwater robots to locate and carefully track marine objects and animals.
A new soft robotic gripper is not only 3D printed in one print, it also doesn't need any electronics to work. The device was developed by a team of roboticists at the University of California San Diego, in collaboration with researchers at the BASF corporation, who detailed their work in Science Robotics.
Robotic Transformer 2 (RT-2) is a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control.
Robotic Transformer 2 (RT-2) is a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control.
Robotic Transformer 2 (RT-2) is a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control.
Robotic Transformer 2 (RT-2) is a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control.
Robotic Transformer 2 (RT-2) is a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control.
Robotic Transformer 2 (RT-2) is a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control.
Robotic Transformer 2 (RT-2) is a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control.
Robotic Transformer 2 (RT-2) is a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control.
Robotic Transformer 2 (RT-2) is a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control.
In a study published in special issue of the journal IET Cyber-Systems and Robotics, researchers from Zhejiang University experienced in legged robot motion and control, pre-trained the neural network (NN) using data from a robot operated by conventional model-based controllers.
Achieving human-level dexterity during manipulation and grasping has been a long-standing goal in robotics. To accomplish this, having a reliable sense of tactile information and force is essential for robots. A recent study, published in IEEE Robotics and Automation Letters, describes the L3 F-TOUCH sensor that enhances the force sensing capabilities of classic tactile sensors. The sensor is lightweight, low-cost, and wireless, making it an affordable option for retrofitting existing robot hands and graspers.