Intelligent power management: Promoting power-consciousness in teams of mobile robots

Kottas, Apostolos; Drenner, Andrew; Papanikolopoulos, Nikolaos

doi:10.1109/robot.2009.5152569

Cited by 16 publications

(3 citation statements)

References 16 publications

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“…Multi-agent cooperative operations have been widely used in military, industrial and civil fields and have gradually been applied in space exploration, disaster rescue and other fields (Cai et al , 2014; Kottas et al , 2009; Wurm et al , 2010). Specifically, in an unknown environment, a multi-agent cooperation system can be used to complete reconnaissance, search and other tasks.…”

Section: Introductionmentioning

confidence: 99%

Multi-robot raster map fusion without initial relative position

Wang,

Cong,

et al. 2023

RIA

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Purpose The purpose of this study is to solve the problem of an unknown initial position in a multi-robot raster map fusion. The method includes two-dimensional (2D) raster maps and three-dimensional (3D) point cloud maps. Design/methodology/approach A fusion method using multiple algorithms was proposed. For 2D raster maps, this method uses accelerated robust feature detection to extract feature points of multi-raster maps, and then feature points are matched using a two-step algorithm of minimum Euclidean distance and adjacent feature relation. Finally, the random sample consensus algorithm was used for redundant feature fusion. On the basis of 2D raster map fusion, the method of coordinate alignment is used for 3D point cloud map fusion. Findings To verify the effectiveness of the algorithm, the segmentation mapping method (2D raster map) and the actual robot mapping method (2D raster map and 3D point cloud map) were used for experimental verification. The experiments demonstrated the stability and reliability of the proposed algorithm. Originality/value This algorithm uses a new visual method with coordinate alignment to process the raster map, which can effectively solve the problem of the demand for the initial relative position of robots in traditional methods and be more adaptable to the fusion of 3D maps. In addition, the original data of the map can come from different types of robots, which greatly improves the universality of the algorithm.

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Section: Introductionmentioning

confidence: 99%

Multi-robot raster map fusion without initial relative position

Wang,

Cong,

et al. 2023

RIA

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“…A similar system was exploited for application in rescue concerning mine disasters [16]. Papanikolopoulos and coworkers have been dedicated to the marsupial robotics for years with contributions on design of miniature robots, docking station, longevity optimization and power management [17]- [20]. Docking is especially important for marsupial robots, which requires accurate control on both relative position and orientation between the child robot and its mother robot.…”

Section: Introductionmentioning

confidence: 99%

A Coordinated Docking Approach Based on Embedded Vision

Zhao¹,

Zhiqiang²,

Gu³

et al. 2016

International Journal of Robotics and Automation

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Docking is an essential yet challenging problem to the deployment of marsupial robotic system involving a mother robot and several child robots, as the technologies such as rail-line tracking and global vision measurement are not suitable for applications in unknown environments. This chapter presents a coordinated docking approach based on embedded vision of the child robot collaborated by the mother robot with an innovative lifting docking station. The child robot utilizes a complementary metal oxide semiconductor (CMOS) camera to capture and extract image features related to a benchmark attached on the docking station, and the internal correlation between its heading direction and the entry direction of docking station is then derived, which makes the docking process be concise and convenient. On this basis, a coordinated docking task model is built and the transition conditions among task states are presented. The precision analysis of the docking is also discussed. The experimental results prove the effectiveness of the proposed approach.

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“…The field of state of charge computation represents a widely explored area with several stable methods developed for reliable state of charge estimation. However, due to the chemical nature of the battery, the challenge for precise calculations is still of current interest for research [211,212].…”

Section: Energy Managementmentioning

confidence: 99%

A novel robotic framework for safe inspection and telemanipulation in hazardous and unstructured environments

Castro¹

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First of all, I would like to express my deep gratitude to my research university supervisor, Professor Manuel Ferre Pérez, for his patient guidance, enthusiastic encouragement and useful critiques of this thesis. An immense thankfulness goes to my research CERN supervisor, Doctor Alessandro Masi, who has believed in my potential and who has always supported me during the last years, being my mentor and my inspiration. Thanks to the unconditional support of Roberto Losito for the direction of the Engineering Department at CERN, that provides extraordinary opportunities and individual development to its scientists. I would like to express my great appreciation and deep respect to Professor Raúl Marín Prades for the support for writing of the thesis, help and profound discussions on teleoperation and robotic controls. Also, I would like to offer my special thanks to my colleagues of the Mechatronics, Robotics and Operation Section within the Survey, Mechatronics and Measurement Group at CERN for their inestimable help in the building-up of this work.

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Intelligent power management: Promoting power-consciousness in teams of mobile robots

Cited by 16 publications

References 16 publications

Multi-robot raster map fusion without initial relative position

Multi-robot raster map fusion without initial relative position

A Coordinated Docking Approach Based on Embedded Vision

A novel robotic framework for safe inspection and telemanipulation in hazardous and unstructured environments

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