Performance analysis of fast marching-based motion planning for autonomous mobile robots in ITER scenarios

Gómez, Javier V.; Vale, Alberto; Garrido, Santiago; Moreno, Luís

doi:10.1016/j.robot.2014.09.016

Cited by 9 publications

(6 citation statements)

References 28 publications

(37 reference statements)

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“…The study findings indicate the effectiveness of sensory systems in reliably detecting ground obstacles. Gómez et al (2015) perform an analysis of optimized trajectories in terms of clearance, smoothness and execution time under hazardous maintenance operations like transportation of equipment for storage, refurbishment and repair. Particularly, the authors examine transport scenarios for AGVs for the planning of operations in the International Thermonuclear Experimental Reactor located at the Cadarache facilities in the south of France.…”

Section: Decision-making At the Tactical Echelonmentioning

confidence: 99%

“…Identification of opportunities for sensors' applicability to improve workforce safety Gázquez et al (2016); Reina et al (2015); Shukla and Karki (2016) Adoption of tools for monitoring and assessing potential hazards Duffy et al (2003); Gómez et al (2015) Operational Ensuring social efficient performance Awuah-Offei (2016); Duffy et al (2003); Krüger et al (2009); Leite et al (2015); Reina et al (2015)…”

Section: Tacticalmentioning

confidence: 99%

See 1 more Smart Citation

Sustainable supply chain management in the digitalisation era: The impact of Automated Guided Vehicles

Bechtsis

Tsolakis

Vlachos

et al. 2017

Journal of Cleaner Production

189

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Internationalization of markets and climate change introduce multifaceted challenges for modern supply chain (SC) management in the today's digitalisation era. On the other hand, Automated Guided Vehicle (AGV) systems have reached an age of maturity that allows for their utilization towards tackling dynamic market conditions and aligning SC management focus with sustainability considerations. However, extant research only myopically tackles the sustainability potential of AGVs, focusing more on addressing network optimization problems and less on developing integrated and systematic methodological approaches for promoting economic, environmental and social sustainability. To that end, the present study provides a critical taxonomy of key decisions for facilitating the adoption of AGV systems into SC design and * Corresponding author. Tel: +30 2310 995896; fax: +30 2310 996018. E-mail address: dimbec@autom.teithe.gr (D. Bechtsis).2 planning, as these are mapped on the relevant strategic, tactical and operational levels of the natural hierarchy. We then propose the Sustainable Supply Chain Cube (S2C2), a conceptual tool that integrates sustainable SC management with the proposed hierarchical decision-making framework for AGVs'. Market opportunities and the potential of integrating AGVs into a SC context with the use of the S2C2 tool are further discussed.

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Section: Decision-making At the Tactical Echelonmentioning

confidence: 99%

Section: Tacticalmentioning

confidence: 99%

Sustainable supply chain management in the digitalisation era: The impact of Automated Guided Vehicles

Bechtsis

Tsolakis

Vlachos

et al. 2017

Journal of Cleaner Production

189

View full text Add to dashboard Cite

show abstract

“…It can be seen in Figure 1(a) that the path obtained using FMM is not safe because it has no clearance from obstacles; nor is it smooth, because it permits abrupt turns along the path. These disadvantages are overcome by the FM 2 method, which we have successfully used with many approaches [24][25][26][27].…”

Section: Algorithm 1 Algorithm Of the Fmmmentioning

confidence: 99%

Nonholonomic Motion Planning Using the Fast Marching Square Method

Arismendi

Álvarez

Garrido

et al. 2015

International Journal of Advanced Robotic Systems

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This research presents two novel approaches to nonholonomic motion planning. The methodologies presented are based on the standard fast marching square path planning method and its application to car-like robots. Under the first method, the environment is considered as a three-dimensional C-space, with the first two dimensions given by the position of the robot and the third dimension by its orientation. This means that we operate over the configuration space instead of the bi-dimensional environment map. Moreover, the trajectory is computed along the C-space taking into account the dimensions of the vehicle, and thus guaranteeing the absence of collisions. The second method uses the standard fast marching square, and takes advantage of the vector field of the velocities computed during the first step of the method in order to adapt the motion plan to the control inputs that a car-like robot is able to execute. Both methods ensure the smoothness and safety of the calculated paths in addition to providing the control actions to perform the trajectory.

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“…The FM 2 has been used for different purposes, such as path planning with mobile vehicles [18], [19], [20] and vehicle formations in 2D [21] and 3D [22] environments, providing optimal trajectories in terms of smoothness and safety.…”

Section: Introductionmentioning

confidence: 99%

Coverage Mission for UAVs Using Differential Evolution and Fast Marching Square Methods

González

Monje

Garrido

et al. 2020

IEEE Aerosp. Electron. Syst. Mag.

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This research presents a novel approach for missions of Coverage Path Planning (CPP) carried out by a UAVs in a 3D environment. These missions are focused on path planning to cover a certain area in an environment in order to carry out tracking, search or rescue tasks. The methodology followed uses an optimization process based on the Differential Evolution (DE) algorithm in combination with the Fast Marching Square (FM 2 ) planner. The DE algorithm evaluates a cost function to determine what the zigzag path with the minimum cost is, according to the steering angle of the zigzag bands (α). This optimization process allows achieving the most optimal zigzag path in terms of distance traveled by the UAV to cover the whole area. Then, the FM 2 method is applied to generate the final path according to the steering angle of the zigzag bands resulting from the DE algorithm. The approach generates a feasible path free from obstacles, keeping a fixed altitude flight over the ground. The flight level, smoothness and safety of the path can be modified by two adjustment parameters included in our approach. Simulated experiments carried out in this work demonstrate that the proposed approach generates the most optimal zigzag path in terms of distance, safety and smoothness to cover a certain whole area, keeping a determined flight level with successful results.

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Performance analysis of fast marching-based motion planning for autonomous mobile robots in ITER scenarios

Cited by 9 publications

References 28 publications

Sustainable supply chain management in the digitalisation era: The impact of Automated Guided Vehicles

Sustainable supply chain management in the digitalisation era: The impact of Automated Guided Vehicles

Nonholonomic Motion Planning Using the Fast Marching Square Method

Coverage Mission for UAVs Using Differential Evolution and Fast Marching Square Methods

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