Criterios de desempeño para evaluar algoritmos de navegación de robots móviles: una revisión

Ceballos, Nelson David Muñoz; Suarez-Rivera, Guiovanny

doi:10.4995/riai.2022.16427

Cited by 4 publications

(3 citation statements)

References 53 publications

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“…Different metrics have been used to asses the effectiveness of the navigation algorithm of the mobile robot (Munoz‐Ceballos & Suarez‐Rivera, 2022). Table 2 shows the metrics used to analyse the performance algorithm, and the values of the variables once the simulation of the disinfection process has finished.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

GBNN algorithm enhanced by movement planner for UV‐C disinfection

Rodrigo,

Sierra‐García,

Santos

2023

Expert Systems

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In order to maintain adequate levels of cleanliness and sanitation in public facilities, prevent the buildup of viruses and other harmful pathogens, and ensure health and safety, health and labor authorities have repeatedly warned of the need to adhere to proper disinfection protocols in the workplace. This is particularly important in public places where food is handled, where there are more vulnerable people, including hospitals and health care centers, or where there is a large concentration of people. One promising approach is the combination of ultraviolet‐C (UV‐C) light and mobile robots to automate disinfection processes. Being this technology effective for disinfection, an excessive dose of UV can damage the materials, limiting its applicability. Therefore, a major challenge for automatic disinfection is to find a route that covers the entire surface, ensures cleanliness, and provides the correct radiation dose while preventing environmental materials from being damaged. To achieve this, in this paper a novel intelligent control approach is proposed. A bio‐inspired Glasius neural network with a motion planner, an UV estimation module, a speed regulator, and pure pursuit controller are combined into one intelligent system. The motion planner proposes a sequence of movements to go through the space in the most efficient way possible, avoiding obstacles of the environment. The speed controller adjusts the dose of UV‐C radiation and the pure pursuit regulator ensures the following of the path. This approach has been tested in various simulation scenarios of increasing complexity and in four different areas of dosing requirements. In simulation, a 44% reduction of the maximum dose is achieved, 17% less distance travelled by the robot and, what is more important, 229% more locations with the appropriate dose.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

GBNN algorithm enhanced by movement planner for UV‐C disinfection

Rodrigo,

Sierra‐García,

Santos

2023

Expert Systems

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“…The gains of the forward kinematic controller is k 1 = [2.0, 1.0] and the backward kinematic controller is k 1 = [1.0, 2.0]. Additionally, according to the metrics for determining the error of a positioning system presented in [40], we evaluated the results of our method using the Mean Squared Error (MSE). Finally, each iteration shown in the result plots represents the run-time of the method and is equivalent to an average of 44 ms each iteration.…”

Section: A Experimental Setupmentioning

confidence: 99%

ViKi-HyCo: A Hybrid-Control Approach for Complex Car-Like Maneuvers

Velasco-Sánchez,

Ángel Muñoz Bañón,

Candelas

et al. 2024

IEEE Access

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While Visual Servoing is deeply studied to perform simple maneuvers, the complex cases where the target is far out of the camera field of view (FOV) during the maneuver are not common in the literature. For this reason, in this paper, we present ViKi-HyCo (Visual Servoing and Kinematic Hybrid-Controller). This approach generates the necessary maneuvers for the complex positioning of a non-holonomic mobile robot in outdoor environments. In this method, we use LiDAR-camera fusion for automatic target calculation. The multi-modal nature of our target representation allows us to hybridize the visual servoing with a kinematic controller. In this way, we can perform complex maneuvers even when the target is far away from the camera's FOV. The automatic target calculation is performed through object localization for outdoor environments, which estimates the spatial location of a target point for the kinematic controller and allows the dynamic calculation of a desired bounding box of the detected object for the visual servoing controller. The proposed approach does not require an object-tracking algorithm and can be applied to any visually tracking robotic task where its kinematic model is known. ViKi-HyCo has an error of 0.0428 ± 0.0467 m in the X-axis and 0.0515 ± 0.0323 m in the Y-axis at the end of a complete positioning task.INDEX TERMS autonomous robots, domestic waste localization, hybrid-control, outdoor environment, sensor fusion, visual servoing.

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“…The success of search and rescue (SAR) missions depends on the performance of robotic platforms individually [ 9 ]. However, search and exploration tasks can be enhanced through cooperative systems using multiple unmanned ground vehicles (UGVs) [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

RUDE-AL: Roped UGV Deployment Algorithm of an MCDPR for Sinkhole Exploration

Orbea,

Cruz Ulloa,

Del Cerro

et al. 2023

Sensors

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The presence of sinkholes has been widely studied due to their potential risk to infrastructure and to the lives of inhabitants and rescuers in urban disaster areas, which is generally addressed in geotechnics and geophysics. In recent years, robotics has gained importance for the inspection and assessment of areas of potential risk for sinkhole formation, as well as for environmental exploration and post-disaster assistance. From the mobile robotics approach, this paper proposes RUDE-AL (Roped UGV DEployment ALgorithm), a methodology for deploying a Mobile Cable-Driven Parallel Robot (MCDPR) composed of four mobile robots and a cable-driven parallel robot (CDPR) for sinkhole exploration tasks and assistance to potential trapped victims. The deployment of the fleet is organized with node-edge formation during the mission’s first stage, positioning itself around the area of interest and acting as anchors for the subsequent release of the cable robot. One of the relevant issues considered in this work is the selection of target points for mobile robots (anchors) considering the constraints of a roped fleet, avoiding the collision of the cables with positive obstacles through a fitting function that maximizes the area covered of the zone to explore and minimizes the cost of the route distance performed by the fleet using genetic algorithms, generating feasible target routes for each mobile robot with a configurable balance between the parameters of the fitness function. The main results show a robust method whose adjustment function is affected by the number of positive obstacles near the area of interest and the shape characteristics of the sinkhole.

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Criterios de desempeño para evaluar algoritmos de navegación de robots móviles: una revisión

Cited by 4 publications

References 53 publications

GBNN algorithm enhanced by movement planner for UV‐C disinfection

GBNN algorithm enhanced by movement planner for UV‐C disinfection

ViKi-HyCo: A Hybrid-Control Approach for Complex Car-Like Maneuvers

RUDE-AL: Roped UGV Deployment Algorithm of an MCDPR for Sinkhole Exploration

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