Intelligent Robot Guidance in Fixed External Camera Network for Navigation in Crowded and Narrow Passages

Ravankar, Abhijeet; Ravankar, Ankit A.; Kobayashi, Yukinori; Emaru, Takanori

doi:10.3390/ecsa-3-d008

Cited by 7 publications

(5 citation statements)

References 5 publications

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“…Dentro del estado del arte este tema es poco abordado por robots autónomos, sin embargo existen algunos desarrollos que usan este concepto de asistencia externa como [31,19,37,34]…”

Section: Sin Contacto -Percepción Externaunclassified

Robótica colaborativa de búsqueda y rescate, una clasificación basada en interacción física

Ulloa¹,

Valero²,

Barrientos³

2022

XLIII Jornadas De Automática: Libro De Actas: 7, 8 Y 9 De Septiembre De 2022, Logroño (La Rioja)

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La Robótica de Búsqueda y Rescate en las últimas décadas ha sido una línea de gran crecimiento, brindando apoyo a brigadas de primera línea en situaciones pos-desastre, aportando principalmente transmisión de información desde zonas de alto riesgo o asistiendo con equipos de primeros auxilios a víctimas. El presente artículo busca establecer una clasificación entre los diferentes tipos de colaboración que pueden generarse entre robots terrestres heterogéneos para tareas de búsqueda y rescate, basado en un criterio planteado según, su interacción física, por los autores. Para ello se han realizado diferentes pruebas mediante robots con diferentes sistemas de locomoción (orugas, patas) en entornos reales que han permitido validar el criterio planteado. Entre las principales situaciones abordadas se destaca el contacto físico directo (Marsupial - Rampa) e indirecto (cables) y sin contacto físico (percepción externa - feromonas) para entornos pos-desastre. De entre las principales ventajas de la robótica colaborativa, extraídas como conclusión en base a este estudio, destacan la capacidad de maximizar las áreas de búsqueda, accediendo a zonas elevadas, explorando cráteres/socavones o asistencia entre robot a través de zonas con oclusiones, de manera similar a como lo haría una brigada de intervención humana.

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“…Dentro del estado del arte este tema es poco abordado por robots autónomos, sin embargo existen algunos desarrollos que usan este concepto de asistencia externa como [31,19,37,34]…”

Section: Sin Contacto -Percepción Externaunclassified

Robótica colaborativa de búsqueda y rescate, una clasificación basada en interacción física

Ulloa¹,

Valero²,

Barrientos³

2022

XLIII Jornadas De Automática: Libro De Actas: 7, 8 Y 9 De Septiembre De 2022, Logroño (La Rioja)

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“…Other approaches include the installation of external cameras to guide the robots through narrow areas where only one at a time can navigate [39], or those less fancy, yet common, approaches based on the restriction of the navigation space in order to exclude areas with potential danger. Among others, environments with the presence of carpets and/or full-length mirrors are usually discarded as zones for proper navigation, as well as those with doorways or corridors too narrow (with respect to the width of the robot) to ensure a smooth navigation [40].…”

Section: Related Workmentioning

confidence: 99%

Automatic Waypoint Generation to Improve Robot Navigation Through Narrow Spaces

Moreno

Monroy

Ruiz-Sarmiento

et al. 2019

Sensors

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In domestic robotics, passing through narrow areas becomes critical for safe and effective robot navigation. Due to factors like sensor noise or miscalibration, even if the free space is sufficient for the robot to pass through, it may not see enough clearance to navigate, hence limiting its operational space. An approach to facing this is to insert waypoints strategically placed within the problematic areas in the map, which are considered by the robot planner when generating a trajectory and help to successfully traverse them. This is typically carried out by a human operator either by relying on their experience or by trial-and-error. In this paper, we present an automatic procedure to perform this task that: (i) detects problematic areas in the map and (ii) generates a set of auxiliary navigation waypoints from which more suitable trajectories can be generated by the robot planner. Our proposal, fully compatible with the robotic operating system (ROS), has been successfully applied to robots deployed in different houses within the H2020 MoveCare project. Moreover, we have performed extensive simulations with four state-of-the-art robots operating within real maps. The results reveal significant improvements in the number of successful navigations for the evaluated scenarios, demonstrating its efficacy in realistic situations.

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“…Virtual pheromones have been proposed to be used for coordinating master-slave robots in References [9,10]. Path planning of multiple robots using information from external security cameras is proposed in Reference [11]. In addition, a direct obstacle coordinate information sharing was proposed in our previous work [12] without considering the uncertainty.…”

Section: Related Workmentioning

confidence: 99%

On Sharing Spatial Data with Uncertainty Integration Amongst Multiple Robots Having Different Maps

Ravankar

Hoshino

et al. 2019

Applied Sciences

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Information sharing is a powerful feature of multi-robot systems. Sharing information precisely and accurately is important and has many benefits. Particularly, smart information sharing can improve robot path planning. If a robot finds a new obstacle or blocked path, it can share this information with other remote robots allowing them to plan better paths. However, there are two problems with such information sharing. First, the maps of the robots may be different in nature (e.g., 2D grid-map, 3D semantic map, feature map etc.) as the sensors used by the robots for mapping and localization may be different. Even the maps generated using the same sensor (e.g., Lidar) can vary in scale or rotation and the sensors used might have different specifications like resolution or range. In such scenarios, the ‘correspondence problem’ in different maps is a critical bottleneck in information sharing. Second, the transience of the obstacles has to be considered while also considering the positional uncertainty of the new obstacles while sharing information. In our previous work, we proposed a ‘node-map’ with a confidence decay mechanism to solve this problem. However, the previous work had many limitations due to the decoupling of new obstacle’s positional uncertainty and confidence decay. Moreover, the previous work applied only to homogeneous maps. In addition, the previous model worked only with static obstacles in the environment. The current work extends our previous work in three main ways: (1) we extend the previous work by integrating positional uncertainty in the confidence decay mechanism and mathematically model the transience of newly added or removed obstacles and discuss its merits; (2) we extend the previous work by considering information sharing in heterogeneous maps build using different sensors; and (3) we consider dynamic obstacles like moving people in the environment and test the proposed method in complex scenarios. All the experiments are performed in real environments and with actual robots and results are discussed.

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Intelligent Robot Guidance in Fixed External Camera Network for Navigation in Crowded and Narrow Passages

Cited by 7 publications

References 5 publications

Robótica colaborativa de búsqueda y rescate, una clasificación basada en interacción física

Robótica colaborativa de búsqueda y rescate, una clasificación basada en interacción física

Automatic Waypoint Generation to Improve Robot Navigation Through Narrow Spaces

On Sharing Spatial Data with Uncertainty Integration Amongst Multiple Robots Having Different Maps

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