Abstract
In the last few decades, several approaches have been presented to accomplish tasks with robots or autonomous systems in a glovebox; nevertheless, in nuclear facilities, risky operations are still executed by humans that guarantee a high manipulation capability and dexterity. Inside the gloveboxes, robotic devices have to operate in cluttered environments, or environments with limited space for movement; therefore, it is of significant interest to identify grasping poses that are feasible within such constrained environments. In this paper, we present and experimentally evaluate a strategy to synthesise optimal grasps considering geometric primitives for a manipulation systems in a constrained environment. The novel strategy has been experimentally evaluated in a cluttered environment (as a glovebox mock-up) with realistic objects, and the efficacy of the proposed grasping algorithm is proposed.
Highlights
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Our work presents an optimisation routine to detect grasping poses in a constrained environment, and we present for the first time a holistic approach that includes the model of the complete manipulation system and extends the work presented in [3,33] where only the hand kinematics are taken into account
We present a strategy to minimise a suitable cost index to synthesise optimal grasping poses within constrained environments for a robotic manipulation system
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Robotics is a key technology for the nuclear industry, which takes an important role for the safe and cost-effective maintenance of safety-critical sections in reactors, research labs and similar places. There is a constant search for new robotic solutions to improve the safety of operations and reduce operational costs [1,2]. Due to the strenuous working conditions, glovebox operations for operators are slow and intensive in terms of the task load. Improving safety and efficiency in glovebox operations have become a new research topic drawing more attention. These new glovebox solutions utilise cutting-edge robotics, AI and computer vision technology to assist the operator during glovebox operations, improve the safety of the operator and increase the overall productivity
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