The Path to Efficiency: Fast Marching Method for Safer, More Efficient Mobile Robot Trajectories

Valero-Gomez, Alberto; Gómez, Javier V.; Garrido, Santiago; Moreno, Luís

doi:10.1109/mra.2013.2248309

Cited by 73 publications

(36 citation statements)

References 18 publications

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“…If a goal point is selected, cost-to-go heuristics could be applied [36], and thus enormously affect the results. Heuristics for FMM, FMMFib and SFMM are straightforward.…”

Section: Several Conclusion Can Be Extracted From the Conducted Expementioning

confidence: 99%

Fast Methods for Eikonal Equations: An Experimental Survey

et al. 2019

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The Fast Marching Method is a very popular algorithm to compute times-of-arrival maps (distances map measured in time units). Since their proposal in 1995, it has been applied to many different applications such as robotics, medical computer vision, fluid simulation, etc. Many alternatives have been proposed with two main objectives: to reduce its computational time and to improve its accuracy. In this paper, we collect the main approaches which improve the computational time of the standard Fast

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“…If a goal point is selected, cost-to-go heuristics could be applied [36], and thus enormously affect the results. Heuristics for FMM, FMMFib and SFMM are straightforward.…”

Section: Several Conclusion Can Be Extracted From the Conducted Expementioning

confidence: 99%

Fast Methods for Eikonal Equations: An Experimental Survey

et al. 2019

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“…Mo can be represented as shown in (14). The area of Cobs is enlarged according to using the method in [9] and the new obstacle space is denoted as Cobs_new.…”

Section: ) Constrained Map Construction and Waypoints Generationmentioning

confidence: 99%

“…To calculate an optimal trajectory, the implementation of deterministic path planning algorithms, such as A* algorithm [5] and fast marching (FM) method [6] is becoming more popular than the stochastic algorithms, such as the genetic [7] and ant colony [8] optimisation algorithms. The FM method has the benefit that can generate a path with improved consistency, completeness and continuity [9]. In order to promote the application on unmanned platforms, especially on USV platform, a number of improvements have also been made on the FM.…”

Section: Introductionmentioning

confidence: 99%

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Aspects of a reliable autonomous navigation and guidance system for an unmanned surface vehicle

Song

Liu

et al. 2016

OCEANS 2016 MTS/IEEE Monterey

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Abstract-This paper describes a novel navigation and guidance (NG) system designed to address the issue of receiving unreliable navigational data considering an unmanned surface vehicles (USVs). In the NG system, a confidence rate determination method has been designed to identify the uncertainty of the acquired data. According to the confidence rate, the risks from inaccurate data can be properly analysed facilitating the system generating a more reliable guidance route. The route is calculated using a newly developed algorithm named the constrained FM*. The new NG system has been verified in simulation environments with results proving the effectiveness and capabilities of the system.

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“…11 In later years, the dynamic window approach 12 has emerged based on the necessity of navigating in dynamic 13 or uncertain 14,15 environments, where most popular navigation methods can be inefficient. 16 Navigation in this case is based on local real-time obstacle avoidance, where onboard sensors can provide information regarding the environment in the robot's neighbourhood.…”

Section: Introductionmentioning

confidence: 99%

Synergistic exploration and navigation of mobile robots under pose uncertainty in unknown environments

Arvanitakis

Tzes

Giannousakis

2018

International Journal of Advanced Robotic Systems

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Path planning under uncertainty in an unknown environment is an arduous task as the resulting map has inaccuracies and a safe path cannot always be found. A path planning method is proposed in unknown environments towards a known target position and under pose uncertainty. A limited range and limited field of view range sensor is considered and the robot pose can be inferred within certain bounds. Based on the sensor measurements a modified map is created to be used for the exploration and path planning processes, taking into account the uncertainty via the calculation of the guaranteed visibility and guaranteed sensed area, where safe navigation can be ensured regardless of the pose-error. A switching navigation function is used to initially explore the space towards the target position, and afterwards, when the target is discovered to navigate the robot towards it. Simulation results highlighting the efficiency of the proposed scheme are presented.

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The Path to Efficiency: Fast Marching Method for Safer, More Efficient Mobile Robot Trajectories

Cited by 73 publications

References 18 publications

Fast Methods for Eikonal Equations: An Experimental Survey

Fast Methods for Eikonal Equations: An Experimental Survey

Aspects of a reliable autonomous navigation and guidance system for an unmanned surface vehicle

Synergistic exploration and navigation of mobile robots under pose uncertainty in unknown environments

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