Hybrid Cells for Multi-Layer Prepreg Composite Sheet Layup

Malhan, Rishi K.; Kabir, Ariyan M.; Shembekar, Aniruddha V.; Shah, Brual C.; Gupta, Satyandra K.; Centea, Timotei

doi:10.1109/coase.2018.8560586

Cited by 15 publications

(7 citation statements)

References 16 publications

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“…Finishing (Bhatt et al, 2019; Kabir et al, 2016, 2018c), painting (Chen et al, 2016), inspection (Yau and Menq, 1995), fiber placement (Malhan et al, 2019a,b, 2018, 2020; Shembekar et al, 2018; Shirinzadeh et al, 2007), sheet forming and handling (Li and Ceglarek, 2002), transportation (Colombo et al, 2019; Kabir et al, 2020; Thakar et al, 2018, 2019a, 2020a,b), grasping (Kumbla et al, 2017, 2018; Thakar et al, 2019b), wire harnessing (Hermansson et al, 2013; Shah and Shah, 2016), machine tending (Al-Hussaini et al, 2020; Annem et al, 2019), and 3D printing (Bhatt et al, 2018) are some of the operations where relative motion of objects can be encoded as path constraints. These path constraints or the motion of the objects can be generated using traditional motion planners (Elber and Cohen, 1994; Kuffner and LaValle, 2000).…”

Section: Introductionmentioning

confidence: 99%

Generation of synchronized configuration space trajectories with workspace path constraints for an ensemble of robots

Kabir

Thakar

Malhan

et al. 2021

The International Journal of Robotics Research

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We present an approach to generate path-constrained synchronous motion for the coupled ensemble of robots. In this article, we refer to serial-link manipulators and mobile bases as robots. We assume that the relative motion constraints among the objects in the environment are given. We represent the motion constraints as path constraints and pose the problem of path-constrained synchronous trajectory generation as a non-linear optimization problem. Our approach generates configuration space trajectories for the robots to manipulate the objects such that the given motion constraints among the objects are satisfied. We present a method that formulates the problem as a discrete parameter optimization problem and solves it using successive constraint refinement techniques. The method adaptively selects the parametric representation of the configuration variables for a given scenario. It also generates an approximate solution as the starting point for the successive constraint refinement stages to reduce the computation time. We discuss in detail why successive constraint refinement strategies are useful for solving this class of problems. We demonstrate the effectiveness of the proposed method on challenging test cases in simulation and physical environments with high-degree-of-freedom robotic systems.

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Section: Introductionmentioning

confidence: 99%

Generation of synchronized configuration space trajectories with workspace path constraints for an ensemble of robots

Kabir

Thakar

Malhan

et al. 2021

The International Journal of Robotics Research

View full text Add to dashboard Cite

show abstract

“…Szcesny et al [47] proposed an innovative approach for automated composite ply placement by employing three industrial manipulators, where two of them were equipped with grippers for material grasping and the third manipulates a mounted compaction roller for layer compression. A comparable hybrid robot cell was developed by Malhan et al [25,26], where rapid refinement of online grasping trajectories was studied. Despite these advances, cooperative/hybrid robotic systems involving mobile robot platforms and fixedbase robotic manipulators have received little attention in the context of advanced composite manufacturing.…”

Section: Introductionmentioning

confidence: 99%

A cooperative mobile robot and manipulator system (Co-MRMS) for transport and lay-up of fibre plies in modern composite material manufacture

Yang

Wong

et al. 2021

Int J Adv Manuf Technol

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Composite materials are widely used in industry due to their light weight and specific performance. Currently, composite manufacturing mainly relies on manual labour and individual skills, especially in transport and lay-up processes, which are time consuming and prone to errors. As part of a preliminary investigation into the feasibility of deploying autonomous robotics for composite manufacturing, this paper presents a case study that investigates a cooperative mobile robot and manipulator system (Co-MRMS) for material transport and composite lay-up, which mainly comprises a mobile robot, a fixed-base manipulator and a machine vision sub-system. In the proposed system, marker-based and Fourier transform-based machine vision approaches are used to achieve high accuracy capability in localisation and fibre orientation detection respectively. Moreover, a particle-based approach is adopted to model material deformation during manipulation within robotic simulations. As a case study, a vacuum suction-based end-effector model is developed to deal with sagging effects and to quickly evaluate different gripper designs, comprising of an array of multiple suction cups. Comprehensive simulations and physical experiments, conducted with a 6-DOF serial manipulator and a two-wheeled differential drive mobile robot, demonstrate the efficient interaction and high performance of the Co-MRMS for autonomous material transportation, material localisation, fibre orientation detection and grasping of deformable material. Additionally, the experimental results verify that the presented machine vision approach achieves high accuracy in localisation (the root mean square error is 4.04 mm) and fibre orientation detection (the root mean square error is 1.84∘) and enables dealing with uncertainties such as the shape and size of fibre plies.

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“…Szcesny et al [13] proposed an innovative approach for automated composite ply placement by employing three industrial manipulators, where two of them were equipped with grippers for material grasping and the third manipulates a mounted compaction roller for layer compression. A comparable hybrid robot cell was developed by Malhan et al [14,15], where rapid refinement of online grasping trajectories was studied. Despite these advances, cooperative/hybrid robotic systems involving mobile robot platforms and fixed-base robotic manipulators have received little attention in the context of advanced composite manufacturing.…”

Section: Introductionmentioning

confidence: 99%

A Cooperative Mobile Robot and Manipulator System (Co-MRMS) for Transport and Lay-up of Fibre Plies in Modern Composite Material Manufacture

Yang

Wong

et al. 2021

Preprint

View full text Add to dashboard Cite

Composite materials are widely used in industry due to their light weight and specific performance. Currently, composite manufacturing mainly relies on manual labour and individual skills, especially in transport and lay-up processes, which are time-consuming and prone to errors. As part of a preliminary investigation into the feasibility of deploying autonomous robotics for composite manufacturing, this paper investigates a cooperative mobile robot and manipulator system (Co-MRMS) for material transport and composite lay-up, which mainly comprises a mobile robot, a fixed-base manipulator and a machine vision sub-system. In the proposed system, marker-based and Fourier transform-based machine vision approaches are used to achieve high accuracy capability in localisation and fibre orientation detection respectively. Moreover, a particle based approach is adopted to model material deformation during manipulation within robotic simulations. As a case study, a vacuum suction based end-effector model is developed to deal with sagging effects and to quickly evaluate different gripper designs, comprising of an array of multiple suction cups. Comprehensive simulations and physical experiments, conducted with a 6-DOF serial manipulator and a two-wheeled differential drive mobile robot, demonstrate the efficient interaction and high performance of the Co-MRMS for autonomous material transportation, material localisation, fibre orientation detection and grasping of deformable material. Additionally, the experimental results verify that the presented machine vision approach achieves high accuracy in localisation (the root mean square error is 4.04 mm) and fibre orientation detection (the root mean square error is 1.84°).

show abstract

Hybrid Cells for Multi-Layer Prepreg Composite Sheet Layup

Cited by 15 publications

References 16 publications

Generation of synchronized configuration space trajectories with workspace path constraints for an ensemble of robots

Generation of synchronized configuration space trajectories with workspace path constraints for an ensemble of robots

A cooperative mobile robot and manipulator system (Co-MRMS) for transport and lay-up of fibre plies in modern composite material manufacture

A Cooperative Mobile Robot and Manipulator System (Co-MRMS) for Transport and Lay-up of Fibre Plies in Modern Composite Material Manufacture

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