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ARQ: Advanced Robotics at Queen Mary

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Robotics for Extreme Environments

The focus of current research is on robots for nuclear environments. The QMUL team is part of the National Centre for Nuclear Robotics (NCNR).

Highly manoeuvrable soft manipulators, grippers and their sensorization

Academics: Kaspar Althoefer

As part of NCNR, we are developing soft manipulators, made from fabrics, that can grow from the tip to tens of metres in length and achieve multiple degrees of freedom bending. These manipulators are compliant and interact safely with the environment and have excellent capabilities of advancing through narrow openings and pipelines. We have developed techniques to precisely control the motion of the manipulators. Complementing the eversion manipulators, we have also created fully collapsible fabric based grippers that weigh under 100g and have a payload of 45N to conduct grasping of tasks. In the domain of grippers, we have also developed new underactuated gripper driven by tendons but has more manoeuvrability than traditional underactuated gripper. These pneumatic and tendon driven systems will greatly enhance the capabilities of conducting manipulation and grasping in constrained and critical areas. 

Complementing these actuation techniques, we are developing low cost bending sensors based on optical fibres that can be embedded into soft grippers to achieve sensory feedback. The low transmission losses in the optical fibres will enable placing the readout electronics far from the soft grippers working in contaminated areas and improve lifetime of these devices. 

Remote structural health monitoring through teleoperation

Academics: Ildar Farkhatdinov, Kaspar Althoefer

In this domain, we are conducting research to utilise manipulators embedded with tactile and optical proximity sensors to intelligently detect and characterize structural degaradation such as  cracks.

In our recent development, we demonstrate one such methodology to classify cracks by sliding a sensorized finger across the surfaces and employing realtime classification. We anticipate selected types of optical fibers will suitable for operation in extreme environments (such as nuclear facilities) where nuclear radiation damages electronic components of commonly employed sensing devices, such as standard force sensors based on strain gauges and video cameras.

Autonomous robotic grasping 

Academics: Lorenzo Jamone

We are developing state-of-art vision-based grasping algorithms for robotic grasping of a wide variety of objects. As part of our translational and integration efforts, we have also developed an extensive benchmark study of existing algorithms as well as a software framework for integrating different manipulation and grasping hardware with control algorithms for rapid testing and deployment. We believe that these results, and the associated software framework, will be valuable in the design of robotic systems for the safe manipulation and disposal of nuclear material.

Analysis Of Cluttered & Occluded Scenes From Millimetre Wave RF Data

Academics: Miles Hansard, Khalid Z. Rajab.

In this project we are developing a millimetre-wave radar system, which could be used to locate objects and robots in hazardous industrial environments. This approach is complementary to camera-based systems, because radar signals can penetrate steam, smoke, and surface debris, which might make the target optically invisible. The project involves traditional radar signal processing algorithms, as well as new machine learning methods. In particular, we show that optical data can be used to improve the spatial calibration of the radar sensors.