Application of the Open Scalable Production System to Machine Tending of Additive Manufacturing Operations by a Mobile Manipulator

Arrais, Rafael; Veiga, Germano; Ribeiro, Tiago T.; Oliveira, Daniel M.; Fernandes, Ramon O.; Conceição, André Gustavo Scolari; Farias, Paulo Cesar Machado de Abreu

doi:10.1007/978-3-030-30244-3_29

Cited by 21 publications

(7 citation statements)

References 9 publications

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“…This effort was integrated on the scope of the H2020 FASTEN project ( (accessed on 17 April 2020), where collaborative mobile manipulators are being developed and deployed for the automation of intralogistics operations in cross-sectorial industrial use cases. Within the FASTEN R&D initiative, the Open Scalable Production System (OSPS) is being developed as a solution for the overall interoperability of CPPS in manufacturing scenarios [ 36 ]. The OSPS promotes connectivity through an Internet of Things (IoT)-based platform to monitor and coordinate collaborative robotic systems to perform machine tending and pick and place operations in logistics warehouses.…”

Section: Resultsmentioning

confidence: 99%

“…As a result, the proposed autonomous exploration system was employed to allow the collaborative robot to have a better sense of its operational environment, and thus, increase the efficiency and reliability of the bin-picking pick and place operation, currently implemented as a set of robotic skills [36]. As to enable the effective integration of the proposed system with the OSPS, it was necessary to migrate the developed system to be compliant with the definition of a robotic skill which is based on the ROS Action paradigm.…”

Section: Test Scenario 3: Industrial Applicationmentioning

confidence: 99%

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Autonomous Scene Exploration for Robotics: A Conditional Random View-Sampling and Evaluation Using a Voxel-Sorting Mechanism for Efficient Ray Casting

Santos

Oliveira

Arrais

et al. 2020

Sensors

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Carrying out the task of the exploration of a scene by an autonomous robot entails a set of complex skills, such as the ability to create and update a representation of the scene, the knowledge of the regions of the scene which are yet unexplored, the ability to estimate the most efficient point of view from the perspective of an explorer agent and, finally, the ability to physically move the system to the selected Next Best View (NBV). This paper proposes an autonomous exploration system that makes use of a dual OcTree representation to encode the regions in the scene which are occupied, free, and unknown. The NBV is estimated through a discrete approach that samples and evaluates a set of view hypotheses that are created by a conditioned random process which ensures that the views have some chance of adding novel information to the scene. The algorithm uses ray-casting defined according to the characteristics of the RGB-D sensor, and a mechanism that sorts the voxels to be tested in a way that considerably speeds up the assessment. The sampled view that is estimated to provide the largest amount of novel information is selected, and the system moves to that location, where a new exploration step begins. The exploration session is terminated when there are no more unknown regions in the scene or when those that exist cannot be observed by the system. The experimental setup consisted of a robotic manipulator with an RGB-D sensor assembled on its end-effector, all managed by a Robot Operating System (ROS) based architecture. The manipulator provides movement, while the sensor collects information about the scene. Experimental results span over three test scenarios designed to evaluate the performance of the proposed system. In particular, the exploration performance of the proposed system is compared against that of human subjects. Results show that the proposed approach is able to carry out the exploration of a scene, even when it starts from scratch, building up knowledge as the exploration progresses. Furthermore, in these experiments, the system was able to complete the exploration of the scene in less time when compared to human subjects.

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Section: Resultsmentioning

confidence: 99%

Section: Test Scenario 3: Industrial Applicationmentioning

confidence: 99%

Autonomous Scene Exploration for Robotics: A Conditional Random View-Sampling and Evaluation Using a Voxel-Sorting Mechanism for Efficient Ray Casting

Santos

Oliveira

Arrais

et al. 2020

Sensors

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“…A prominent case can be found in ref. [29], where controllers for VPF based on NMPC were responsible for essential navigation tasks in a case study of additive manufacturing operations by a mobile manipulator within a practical application. 2 However, the path does not necessarily need to be physical.…”

Section: Nmpc-based Visual Path Following Control With Variable Perce...mentioning

confidence: 99%

NMPC-based visual path following control with variable perception horizon

2023

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For greater autonomy of visual control-based solutions, especially applied to mobile robots, it is necessary to consider the existence of unevenness in the navigation surface, an intrinsic characteristic of several real applications. In general, depth information is essential for navigating three-dimensional environments and for the consistent parameter calibration of the visual models. This work proposes a new solution, including depth information in the visual path-following (VPF) problem, which allows the variation of the perception horizon at runtime while forcing the coupling between optical and geometric quantities. A new NMPC (nonlinear model predictive control) framework considering the addition of a new input to an original solution for the constrained VPF-NMPC allows the maintenance of low computational complexity. Experimental results in an outdoor environment with a medium-sized commercial robot demonstrate the correctness of the proposal.

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“…The orchestration of the tasks between the mobile platform and the Kuka arm is established using a software package named Task Manager (TM), introduced by authors in [11].…”

Section: B Software Architecturementioning

confidence: 99%

Force control heuristics for surpassing pose uncertainty in mobile robotic assembly platforms

Moutinho

Rebelo

Costa

et al. 2021

2021 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

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Application of the Open Scalable Production System to Machine Tending of Additive Manufacturing Operations by a Mobile Manipulator

Cited by 21 publications

References 9 publications

Autonomous Scene Exploration for Robotics: A Conditional Random View-Sampling and Evaluation Using a Voxel-Sorting Mechanism for Efficient Ray Casting

Autonomous Scene Exploration for Robotics: A Conditional Random View-Sampling and Evaluation Using a Voxel-Sorting Mechanism for Efficient Ray Casting

NMPC-based visual path following control with variable perception horizon

Force control heuristics for surpassing pose uncertainty in mobile robotic assembly platforms

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