Intuitive Programming with Remotely Instructed Robots inside Future Gloveboxes

Ghosh, Ayan; Veres, Sándor M.; Daniel, Paredes-Soto; Clarke, James E.; Rossiter, J.A.

doi:10.1145/3371382.3378326

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…Moreover, due to safety concerns, human-inthe-loop solutions are deemed to be more desirable at least in early phases of deployment. Novel technologies in robotics and artificial intelligence can be exploited to increase the safety in the legacy glovebox or to design new robotic gloveboxes [6][7][8]; in both cases, dexterous robotic manipulators, sensors, and control algorithms can avoid direct contact between the operator and hazardous material. Inside the unstructured environment of gloveboxes, robots could be controlled by the operator via teleoperation while more autonomous control strategies could be exploited in more standard tasks.…”

Section: Introductionmentioning

confidence: 99%

Robot-Assisted Glovebox Teleoperation for Nuclear Industry

et al. 2021

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The nuclear industry has some of the most extreme environments in the world, with radiation levels and extremely harsh conditions restraining human access to many facilities. One method for enabling minimal human exposure to hazards under these conditions is through the use of gloveboxes that are sealed volumes with controlled access for performing handling. While gloveboxes allow operators to perform complex handling tasks, they put operators at considerable risk from breaking the confinement and, historically, serious examples including punctured gloves leading to lifetime doses have occurred. To date, robotic systems have had relatively little impact on the industry, even though it is clear that they offer major opportunities for improving productivity and significantly reducing risks to human health. This work presents the challenges of robotic and AI solutions for nuclear gloveboxes, and introduces a step forward for bringing cutting-edge technology to gloveboxes. The problem statement and challenges are highlighted and then an integrated demonstrator is proposed for robotic handling in nuclear gloveboxes for nuclear material handling. The proposed approach spans from tele-manipulation to shared autonomy, computer vision solutions for robotic manipulation to machine learning solutions for condition monitoring.

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Section: Introductionmentioning

confidence: 99%