Widespread backing for UK robotics network

The Engineering and Physical Sciences Research Council (EPSRC) has announced the launch of a new robotics network that aims to foster academic and industry collaboration. The UK Robotics and Autonomous Systems Network (UK-RAS Network) will have a strong academic foundation, with a number of universities acting as founding members. According to the EPSRC, the network has already received strong support from major industrial partners, as well as from professional bodies such as Royal Academy of Engineering, IET, and The Institute of Mechanical Engineers. Globally, the market for service and industrial robots is estimated to reach $59.5 billion by 2020. A primary aim of the network will be to bring the UK’s academic capabilities under national coordination, fuelling innovation in the robotics sector and taking advantage of the growth in the industry.   Cont'd...  

CLEARPATH ROBOTICS ANNOUNCES MOBILITY SOLUTION FOR RETHINK ROBOTICS' BAXTER ROBOT

Clearpath Robotics announced the newest member of its robot fleet: an omnidirectional development platform called Ridgeback. The mobile robot is designed to carry heavy payloads and easily integrate with a variety of manipulators and sensors. Ridgeback was unveiled as a mobile base for Rethink Robotics' Baxter research platform at ICRA 2015 in Seattle, Washington.  "Many of our customers have approached us looking for a way to use Baxter for mobile manipulation research - these customers inspired the concept of Ridgeback. The platform is designed so that Baxter can plug into Ridgeback and go," said Julian Ware, General Manager for Research Products at Clearpath Robotics. "Ridgeback includes all the ROS, visualization and simulation support needed to start doing interesting research right out of the box."  Ridgeback's rugged drivetrain and chassis is designed to move manipulators and other heavy payloads with ease. Omnidirectional wheels provide precision control for forward, lateral or twisting movements in constrained environments. Following suit of other Clearpath robots, Ridgeback is ROS-ready and designed for rapid integration of sensors and payloads; specific consideration has been made for the integration of the Baxter research platform.

QinetiQ North America Introduces DriveRobotics

From QinetiQ North America: By transforming manned industrial vehicles into unmanned robots, DriveRobotics™ add-on applique kit lets building demolition and roadside construction companies convert to unmanned operations whenever operators face hazardous situations. This commercial robotic system, which can also be installed in new vehicles and existing fleets, eliminates need for spotter. Remote-control capabilities enable or facilitate machine use in demanding applications... ( full press release )

Gear Generator

  About Gear Generator: Gear Generator is a tool for creating involute spur gearsand download them in SVG format. In addition it let you compose full gear layouts with connetcted gears to design multiple gears system with control of the input/output ratio and rotation speed. Gears can be animated with various speed to demonstrate working mechanism... ( link )

Yale OpenHand Project

From Yale's OpenHand Project: This project intends to establish a series of open-source hand designs, and through the contributions of the open-source user community, result in a large number of useful design modifications and variations available to researchers. Based on the original  SDM Hand , the  Model T  is the OpenHand Project's first released hand design, initially introduced at ICRA 2013. the four underactuated fingers are differentially coupled through a floating pulley tree, allowing for equal force output on all finger contacts. Based on our lab's work with iRobot and Harvard on the  iHY hand , which won the  DARPA ARM program , the  Model O  replicates the hand topology common to several commercial hands, including ones from Barrett, Robotiq, and Schunk (among others). A commercial version of this hand is currently for sale by  RightHand Robotics ... ( homepage )

Robo.Op: Opening Industrial Robotics

From MADLAB.CC: Robo.Op is an open hardware / open software platform for hacking industrial robots (IRs). Robo.Op makes it cheaper and easier to customize your IR for creative use, so you can explore the fringes of industrial robotics. The toolkit is made up of a modular physical prototyping platform, a simplified software interface, and a centralized hub for sharing knowledge, tools, and code... ( homepage ) ( github )  

VERSABALL Beer Pong Robot

From Empire Robotics: The VERSABALL is a squishy balloon membrane full of loose sub-millimeter particles. The soft ball gripper easily conforms around a wide range of target object shapes and sizes. Using a process known as “granular jamming”, air is quickly sucked out of the ball, which vacuum-packs the particles and hardens the gripper around the object to hold and lift it. The object releases when the ball is re-inflated. VERSABALL comes in multiple head shapes and sizes that use the same pneumatic base... ( Empire Robotics' site )

Robot Learning Manipulation Action Plans by "Watching" Unconstrained Videos from the World Wide Web

From Yezhou Yang, Yi Li, Cornelia Fermuller and Yiannis Aloimonos: In order to advance action generation and creation in robots beyond simple learned schemas we need computational tools that allow us to automatically interpret and represent human actions. This paper presents a system that learns manipulation action plans by processing unconstrained videos from the World Wide Web. Its goal is to robustly generate the sequence of atomic actions of seen longer actions in video in order to acquire knowledge for robots. The lower level of the system consists of two convolutional neural network (CNN) based recognition modules, one for classifying the hand grasp type and the other for object recognition. The higher level is a probabilistic manipulation action grammar based parsing module that aims at generating visual sentences for robot manipulation. The list of the grasping types. Experiments conducted on a publicly available unconstrained video dataset show that the system is able to learn manipulation actions by “watching” unconstrained videos with high accuracy.... ( article at Kurzweilai.net ) ( original paper )

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