Decentralized active information acquisition: Theory and application to multi-robot SLAM

Atanasov, Nikolay; Ny, Jérôme Le; Daniilidis, Kostas; Pappas, George J.

doi:10.1109/icra.2015.7139863

Cited by 159 publications

(166 citation statements)

References 26 publications

Supporting

Mentioning

165

Contrasting

Unclassified

Order By: Relevance

“…Other noteworthy approaches are by Atanasov et al (2015), who focus on decentralized multi-sensor information acquisition, and Freundlich et al (2013), who plan the next-best-view to reduce the localization uncertainty of a group of stationary targets.…”

Section: Related Workmentioning

confidence: 99%

Information-Driven Autonomous Exploration for a Vision-Based Mav

Palazzolo

Stachniss

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:Most micro aerial vehicles (MAV) are flown manually by a pilot. When it comes to autonomous exploration for MAVs equipped with cameras, we need a good exploration strategy for covering an unknown 3D environment in order to build an accurate map of the scene. In particular, the robot must select appropriate viewpoints to acquire informative measurements. In this paper, we present an approach that computes in real-time a smooth flight path with the exploration of a 3D environment using a vision-based MAV. We assume to know a bounding box of the object or building to explore and our approach iteratively computes the next best viewpoints using a utility function that considers the expected information gain of new measurements, the distance between viewpoints, and the smoothness of the flight trajectories. In addition, the algorithm takes into account the elapsed time of the exploration run to safely land the MAV at its starting point after a user specified time. We implemented our algorithm and our experiments suggest that it allows for a precise reconstruction of the 3D environment while guiding the robot smoothly through the scene.

show abstract

Section: Related Workmentioning

confidence: 99%

Information-Driven Autonomous Exploration for a Vision-Based Mav

Palazzolo

Stachniss

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…Using a group of mobile robots equipped with sensors for source concentration measurement, the mobile robots team cooperatively estimates the gradient of the exploration field, moves to the objects of interest, and keeps a predefined formation in movement [8]. Atanasov et al [9] developed an acquisition method of multisensors active information capturing the common characteristics of these scenarios and controlling mobile sensing systems to improve the accuracy and efficiency of collecting information autonomously.…”

Section: Introductionmentioning

confidence: 99%

“…Multiple robots cooperatively acquired the surrounding's information in wide research work [1,[6][7][8][9], and an integration strategy of different kinds of measurements was used in multimode sense of 3D perception. Pfingsthorn et al [7] updated the local submaps through their graph-based structures, and made it be efficiently communicated among mobile robots' sensors.…”

Section: Introductionmentioning

confidence: 99%

Information-Fusion Methods Based Simultaneous Localization and Mapping for Robot Adapting to Search and Rescue Postdisaster Environments

Wang

Zhang

Song

et al. 2018

Journal of Robotics

View full text Add to dashboard Cite

The first application of utilizing unique information-fusion SLAM (IF-SLAM) methods is developed for mobile robots performing simultaneous localization and mapping (SLAM) adapting to search and rescue (SAR) environments in this paper. Several fusion approaches, parallel measurements filtering, exploration trajectories fusing, and combination sensors' measurements and mobile robots' trajectories, are proposed. The novel integration particle filter (IPF) and optimal improved EKF (IEKF) algorithms are derived for information-fusion systems to perform SLAM task in SAR scenarios. The information-fusion architecture consists of multirobots and multisensors (MAM); multiple robots mount on-board laser range finder (LRF) sensors, localization sonars, gyro odometry, Kinect-sensor, RGB-D camera, and other proprioceptive sensors. This information-fusion SLAM (IF-SLAM) is compared with conventional methods, which indicates that fusion trajectory is more consistent with estimated trajectories and real observation trajectories. The simulations and experiments of SLAM process are conducted in both cluttered indoor environment and outdoor collapsed unstructured scenario, and experimental results validate the effectiveness of the proposed informationfusion methods in improving SLAM performances adapting to SAR scenarios.

show abstract

“…As can be reviewed in works like [1] or [12] robot collaboration usually presents a decentralized architecture in which robots exchanges mission-related information. Consequently, sharing information allows optimizing the mission execution [158].…”

Section: Environment Formalization and Interactionmentioning

confidence: 99%

“…Consequently, sharing information allows optimizing the mission execution [158]. Therefore, it can be found several approaches focused on collaborative sensing [12], detection and tracking [141] or exploration [32]. Robot collaboration group are usually developed as identical or similar platforms [44].…”

Section: Environment Formalization and Interactionmentioning

confidence: 99%

Mission-Oriented Heterogeneous Robot Cooperation Based on Smart Resources Execution

Sánchez¹

View full text Add to dashboard Cite

Home environments are changing as more technological devices are used to improve daily life. The growing demand for high technology in our homes means that robot integration will soon arrive. Home devices are evolving in a connected paradigm in which data flows to perform efficient home task management. Heterogeneous home robots connected in a network can establish a workflow that complements their capabilities and so increases performance within a mission execution. This work addresses the definition and requirements of a robot-group mission in the home context. The proposed solution relies on a network of smart resources, which are defined as cyber-physical systems that provide high-level service execution. Firstly, control middleware architecture is introduced as the execution base for the Smart resources.Next, the Smart resource topology and its integration within a robotic platform are addressed. Services supplied by Smart resources manage their execution through a robot behavior architecture. Robot behavior execution is hierarchically organized through a mission definition that can be established as an individual or collective approach. Environment model and interaction tasks characterize the operation capabilities of each robot within a mission. Mission goal achievement in a heterogeneous group is enhanced through the complement of the interaction capabilities of each robot. To offer a clearer explanation, a full use case is presented in which two robots cooperate to execute a mission and the previously detailed steps are evaluated. Finally, some of the obtained results are discussed as conclusions and future works is introduced. ResumenLos entornos domésticos se encuentran sometidos a un proceso de cambio gracias al empleo de dispositivos tecnológicos que mejoran la calidad de vida de las personas. La creciente demanda de alta tecnología en los hogares señala una próxima incorporación de la robótica de servicio. Los dispositivos domésticos están evolucionando hacia un paradigma de conexión en el cual la información fluye para ofrecer una gestión más eficiente. En este entorno, robots heterogéneos conectados a la red pueden establecer un flujo de trabajo que ofreciendo nuevas soluciones y incrementando la eficiencia en la ejecución de tareas. Este trabajo aborda la definición y los requisitos necesarios para la ejecución de misiones en grupos de robots heterogéneos en entornos domésticos. La solución propuesta se apoya en una red de Smart resources, que son definidos como sistemas ciber-físicos que proporcionan servicios de alto nivel. En primer lugar, se presenta la arquitectura del middleware de control en la cual se basa la ejecución de los Smart resources. A continuación se detalla la topología de los Smart resources, así como su integración en plataformas robóticas. Los servicios proporcionados por los Smart resources gestionan su ejecución mediante una arquitectura de comportamientos para robots. La ejecución de estos comportamientos se organiza de forma jerárquica mediante la definición de ...

show abstract

Decentralized active information acquisition: Theory and application to multi-robot SLAM

Cited by 159 publications

References 26 publications

Information-Driven Autonomous Exploration for a Vision-Based Mav

Information-Driven Autonomous Exploration for a Vision-Based Mav

Information-Fusion Methods Based Simultaneous Localization and Mapping for Robot Adapting to Search and Rescue Postdisaster Environments

Mission-Oriented Heterogeneous Robot Cooperation Based on Smart Resources Execution

Contact Info

Product

Resources

About