scholarly journals Innovative Mobile Manipulator Solution for Modern Flexible Manufacturing Processes

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5414 ◽  
Author(s):  
Jose Luis Outón ◽  
Iván Villaverde ◽  
Héctor Herrero ◽  
Urko Esnaola ◽  
Basilio Sierra
Keyword(s):  
Mass Customization ◽  
Paradigm Shift ◽  
Flexible Manufacturing ◽  
Autonomous Navigation ◽  
Dynamic Environments ◽  
Mobile Manipulator ◽  
New Production ◽  
Security Systems ◽  
Current Mass ◽  
Human Operators

There is a paradigm shift in current manufacturing needs that is causing a change from the current mass-production-based approach to a mass customization approach where production volumes are smaller and more variable. Current processes are very adapted to the previous paradigm and lack the required flexibility to adapt to the new production needs. To solve this problem, an innovative industrial mobile manipulator is presented. The robot is equipped with a variety of sensors that allow it to perceive its surroundings and perform complex tasks in dynamic environments. Following the current needs of the industry, the robot is capable of autonomous navigation, safely avoiding obstacles. It is flexible enough to be able to perform a wide variety of tasks, being the change between tasks done easily thanks to skills-based programming and the ability to change tools autonomously. In addition, its security systems allow it to share the workspace with human operators. This prototype has been developed as part of THOMAS European project, and it has been tested and demonstrated in real-world manufacturing use cases.

scholarly journals A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1276
Author(s):  
Jose Luis Outón ◽  
Ibon Merino ◽  
Iván Villaverde ◽  
Aitor Ibarguren ◽  
Héctor Herrero ◽  
...  
Keyword(s):  
Cognitive Skills ◽  
Autonomous Navigation ◽  
Added Value ◽  
Mobile Manipulator ◽  
Task Management ◽  
3D Perception ◽  
Cooperative Tasks ◽  
Human Operators ◽  
Industrial Context ◽  
And Task

In modern industry there are still a large number of low added-value processes that can be automated or semi-automated with safe cooperation between robot and human operators. The European SHERLOCK project aims to integrate an autonomous industrial mobile manipulator (AIMM) to perform cooperative tasks between a robot and a human. To be able to do this, AIMMs need to have a variety of advanced cognitive skills like autonomous navigation, smart perception and task management. In this paper, we report the project’s tackle in a paradigmatic industrial application combining accurate autonomous navigation with deep learning-based 3D perception for pose estimation to locate and manipulate different industrial objects in an unstructured environment. The proposed method presents a combination of different technologies fused in an AIMM that achieve the proposed objective with a success rate of 83.33% in tests carried out in a real environment.

scholarly journals Sensor Fusion-Based Approach to Eliminating Moving Objects for SLAM in Dynamic Environments

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 230
Author(s):  
Xiangwei Dang ◽  
Zheng Rong ◽  
Xingdong Liang
Keyword(s):  
State Estimation ◽  
Autonomous Navigation ◽  
Moving Objects ◽  
Physical Simulation ◽  
Point Clouds ◽  
Dynamic Environments ◽  
Accurate Localization ◽  
Novel Approach ◽  
Localization And Mapping ◽  
Real World Datasets

Accurate localization and reliable mapping is essential for autonomous navigation of robots. As one of the core technologies for autonomous navigation, Simultaneous Localization and Mapping (SLAM) has attracted widespread attention in recent decades. Based on vision or LiDAR sensors, great efforts have been devoted to achieving real-time SLAM that can support a robot’s state estimation. However, most of the mature SLAM methods generally work under the assumption that the environment is static, while in dynamic environments they will yield degenerate performance or even fail. In this paper, first we quantitatively evaluate the performance of the state-of-the-art LiDAR-based SLAMs taking into account different pattens of moving objects in the environment. Through semi-physical simulation, we observed that the shape, size, and distribution of moving objects all can impact the performance of SLAM significantly, and obtained instructive investigation results by quantitative comparison between LOAM and LeGO-LOAM. Secondly, based on the above investigation, a novel approach named EMO to eliminating the moving objects for SLAM fusing LiDAR and mmW-radar is proposed, towards improving the accuracy and robustness of state estimation. The method fully uses the advantages of different characteristics of two sensors to realize the fusion of sensor information with two different resolutions. The moving objects can be efficiently detected based on Doppler effect by radar, accurately segmented and localized by LiDAR, then filtered out from the point clouds through data association and accurate synchronized in time and space. Finally, the point clouds representing the static environment are used as the input of SLAM. The proposed approach is evaluated through experiments using both semi-physical simulation and real-world datasets. The results demonstrate the effectiveness of the method at improving SLAM performance in accuracy (decrease by 30% at least in absolute position error) and robustness in dynamic environments.

scholarly journals Validation of a Dynamic Planning Navigation Strategy Applied to Mobile Terrestrial Robots

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4322 ◽  
Author(s):  
Caroline Silva ◽  
Átila de Oliveira ◽  
Marcelo Fernandes
Keyword(s):  
Genetic Algorithm ◽  
Population Size ◽  
Autonomous Navigation ◽  
Genetic Parameters ◽  
Dynamic Environments ◽  
Dynamic Planning ◽  
Navigation Algorithm ◽  
Navigation Strategy ◽  
Terrestrial Environments ◽  
Simulation Results

This work describes the performance of a DPNA-GA (Dynamic Planning Navigation Algorithm optimized with Genetic Algorithm) algorithm applied to autonomous navigation in unknown static and dynamic terrestrial environments. The main aim was to validate the functionality and robustness of the DPNA-GA, with variations of genetic parameters including the crossover rate and population size. To this end, simulations were performed of static and dynamic environments, applying the different conditions. The simulation results showed satisfactory efficiency and robustness of the DPNA-GA technique, validating it for real applications involving mobile terrestrial robots.

scholarly journals A Robust RANSAC-Based Planet Radius Estimation for Onboard Visual Based Navigation

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 4041
Author(s):  
Francesco de Gioia ◽  
Gabriele Meoni ◽  
Gianluca Giuffrida ◽  
Massimiliano Donati ◽  
Luca Fanucci
Keyword(s):  
Autonomous Navigation ◽  
Navigation Systems ◽  
Processing Pipeline ◽  
Ground Station ◽  
Noise Image ◽  
Simple Processing ◽  
Best Fitting ◽  
Body Center ◽  
Human Operators ◽  
Multiple Spacecraft

Individual spacecraft manual navigation by human operators from ground station is expected to be an emerging problem as the number of spacecraft for space exploration increases. Hence, as an attempt to reduce the burden to control multiple spacecraft, future missions will employ smart spacecraft able to navigate and operate autonomously. Recently, image-based optical navigation systems have proved to be promising solutions for inexpensive autonomous navigation. In this paper, we propose a robust image processing pipeline for estimating the center and radius of planets and moons in an image taken by an on-board camera. Our custom image pre-processing pipeline is tailored for resource-constrained applications, as it features a computationally simple processing flow with a limited memory footprint. The core of the proposed pipeline is a best-fitting model based on the RANSAC algorithm that is able to handle images corrupted with Gaussian noise, image distortions, and frame drops. We report processing time, pixel-level error of estimated body center and radius and the effect of noise on estimated body parameters for a dataset of synthetic images.

Agile Holonic Network Organizations

2011 ◽  
pp. 35-42 ◽  
Author(s):  
Paul T. Kidd
Keyword(s):  
Mass Customization ◽  
Paradigm Shift ◽  
Information Society ◽  
Business Environment ◽  
New Paradigm ◽  
The World ◽  
Network Organizations ◽  
Post Industrial

Enterprises have been radically altered since the 1980s, so much so that people talk about a new paradigm, which is referred to by different names such as post- Fordism, post-industrial era, mass customization, information society, etc. However, awareness of this paradigm shift is not a new phenomenon since it has been extensively discussed in the literature since the 1970s (e.g., see Kidd, 1994; Piore & Sable, 1984; Savage, 1996; Toffler, 1971). That the world of enterprise is undergoing a paradigm shift is not of great interest anymore. Of more importance are the details of the new and advanced concepts that are required in the longer-term to deal with an ever-changing business environment.

MODERN APPROACHES OF INDUSTRIAL ENTERPRISES TO USE FLEXIBLE PRODUCTION METHODS

2020 ◽  
Vol 4 (10) ◽  
pp. 32-36
Author(s):  
O. V. TITOVA ◽  
Keyword(s):  
Production System ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Modern World ◽  
Flexible Production ◽  
New Production ◽  
Production Methods ◽  
Industrial Enterprises ◽  
Selection Of

The article shows that the success of a production system depends on the ability to effectively change its internal structure in connection with any change in demand or technology. Investing in a new production system as well as modifying an existing system requires informed decisions. Moreover, in a competitive envi-ronment, one of the key decisions that a manufacturing enterprise must make is the selection of appropriate manufacturing systems. The main feature of a flexible manufacturing system, which helps differentiate it from conventional manufacturing systems, is its ability to respond effectively to changes in product type through different flexibilities. Flexible manufacturing systems are well used in the manufacturing world as well as in all industries. Basic information about this technology is very important, because a flexible production system is involved in almost everything that is needed in the modern world.

scholarly journals Human Modeling for Efficient Predictive Collision Detection

2020 ◽  
Vol 22 ◽  
Author(s):  
Gabriel Streitmatter
Keyword(s):  
Collision Detection ◽  
Flexible Manufacturing ◽  
Dynamic Environments ◽  
The Body ◽  
Time Data ◽  
Look Ahead ◽  
Human Modeling ◽  
Sequential Samples ◽  
Swept Volume ◽  
Human Robot Collaboration

As demands on manufacturing rapidly evolve, flexible manufacturing is becoming more essential for acquiring the necessary productivity to remain competitive. An innovative approach to flexible manufacturing is the introduction of fenceless robotic manufacturing cells to acquire and leverage greater human-robot collaboration (HRC). This involves operations in which a human and a robot share a space, complete tasks together, and interact with each other. Such operations, however, pose serious safety concerns. Before HRC can become a viable possibility, robots must be capable of safely operating within and responding to events in dynamic environments. Furthermore, the robot must be able to do this quickly during online operation. This paper outlines an algorithm for predictive collision detection. This algorithm gives the robot the ability to look ahead at its trajectory, and the trajectories of other bodies in its environment and predict potential collisions. The algorithm approximates a continuous swept volume of any articulated body along its trajectory by taking only a few time sequential samples of the predicted orientations of the body and creating surfaces that patch the orientations together with Coons patches. Run time data collected on this algorithm suggest that the algorithm can accurately predict future collisions in under 30 ms.

scholarly journals Exponential Fields Formulation for WMR Navigation

2012 ◽  
Vol 9 (4) ◽  
pp. 375-397 ◽  
Author(s):  
Edgar A. Martínez-García ◽  
Rafael Torres-Cordoba
Keyword(s):  
Autonomous Navigation ◽  
Sensory Information ◽  
Dynamic Environments ◽  
Force Model ◽  
Social Force ◽  
Wheeled Mobile Robots ◽  
Navigation Algorithm ◽  
The Social ◽  
Planning Scheme ◽  
Fast Dynamic

In this manuscript, an autonomous navigation algorithm for wheeled mobile robots (WMR) operating in dynamic environments (indoors or structured outdoors) is formulated. The planning scheme is of critical importance for autonomous navigational tasks in complex dynamic environments. In fast dynamic environments, path planning needs algorithms able to sense simultaneously a diversity of obstacles, and use such sensory information to improve real-time navigation control, while moving towards a desired goal destination. The framework tackles 4 issues. 1) Reformulation of the Social Force Model (SFM) adapted to WMR; 2) the cohesion of a general inertial scheme to represents motion in any coordinate system; 3) control of actuators rotational speed as a general model regardless kinematic restrictions; 4) assuming detection of features (obstacles/goals), adaptive numeric weights are formulated to affect navigational exponential components. Simulation and experimental outdoors results are presented to show the feasibility of the proposed framework.

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