Identifying optimal trajectory parameters in robotic finishing operations using minimum number of physical experiments

Kabir, Ariyan M.; Langsfeld, Joshua D.; Kaipa, Krishnanand N.; Gupta, Satyandra K.

doi:10.3233/ica-180563

Cited by 8 publications

(3 citation statements)

References 41 publications

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“…While such a system should support a range of industrial tasks, we focused our initial implementation on sanding. The choice was mainly based on the prevalence of sanding tasks in industrial applications and the recent interest in flexible robot sanding platforms in the research literature [26,33] and industry (e.g., GrayMatter Robotics [1] and Norbo Robotics [2]). Additionally, sanding tasks are a desirable candidate for human-robot teaming given the physical challenges of manual sanding and the high degree of process variability that makes broad robotic automation challenging.…”

Section: Integration and Workflowsmentioning

confidence: 99%

A System for Human-Robot Teaming through End-User Programming and Shared Autonomy

Hagenow,

Senft,

Radwin

et al. 2024

Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction

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Many industrial tasks-such as sanding, installing fasteners, and wire harnessing-are difficult to automate due to task complexity and variability. We instead investigate deploying robots in an assistive role for these tasks, where the robot assumes the physical task burden and the skilled worker provides both the high-level task planning and low-level feedback necessary to effectively complete the task. In this article, we describe the development of a system for flexible human-robot teaming that combines state-of-the-art methods in end-user programming and shared autonomy and its implementation in sanding applications. We demonstrate the use of the system in two types of sanding tasks, situated in aircraft manufacturing, that highlight two potential workflows within the human-robot teaming setup. We conclude by discussing challenges and opportunities in human-robot teaming identified during the development, application, and demonstration of our system. CCS CONCEPTS• Human-centered computing → Collaborative interaction; • Computer systems organization → Robotic autonomy.

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Section: Integration and Workflowsmentioning

confidence: 99%

A System for Human-Robot Teaming through End-User Programming and Shared Autonomy

Hagenow,

Senft,

Radwin

et al. 2024

Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction

View full text Add to dashboard Cite

show abstract

“…The CollisionScore is considered in third stage by setting w 5 > 0 in (5). We conducted experiments across the test cases described in Section 5 and used active learning inspired adaptive search (Kabir et al, 2018a, 2017), to identify the weights ( w 1 – w 5 ) such that the computation time is minimized without compromising solution quality. This reduces the overhead of identifying appropriate Lagrange-multipliers from the optimization routine.…”

Section: Approachmentioning

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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“…Modern robotics imposes the solution of complex tasks such as industrial operations [27,22,56], speech recognition [18], machine-human interaction [30] and navigation [47,21,23]. Within this context, machine vision tasks are very challenging and fundamental, see [16,26].…”

Section: Introductionmentioning

confidence: 99%

A multi-aperture optical flow estimation method for an artificial compound eye

Zhang

Neri

et al. 2019

ICA

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An artificial compound eye (ACE) is a bio-inspired vision sensor which mimics a natural compound eye (typical of insects). This artificial eye is able to visualize large fields of the outside world through multi-aperture. Due to its functioning, the ACE is subject to optical flow, that is an apparent motion of the object visualized by the eye. This paper proposes a method to estimate the optical flow based on capturing multiple images (multi-aperture).In this method, based on descriptors-based initial optical flows, a unified global energy function is presented to incorporate the information of multi-aperture and simultaneously recover the optical flows of multi-aperture. The energy function imposes a compound flow fields consistency assumption along with the brightness constancy and piecewise smoothness assumptions. This formula efficiently binds the flow field in time and space, and further enables view-consistent optical flow estimation. Experimental results on real and synthetic data demonstrate that the proposed method recovers view-consistent optical flows crossed multi-aperture and performs better than other optical flow methods on the multi-aperture images.

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Identifying optimal trajectory parameters in robotic finishing operations using minimum number of physical experiments

Cited by 8 publications

References 41 publications

A System for Human-Robot Teaming through End-User Programming and Shared Autonomy

A System for Human-Robot Teaming through End-User Programming and Shared Autonomy

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

A multi-aperture optical flow estimation method for an artificial compound eye

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