Multi-robot exploration for search and rescue missions: A report of map building in RoboCupRescue 2009

Nagatani, Keiji; Okada, Yoshito; Tokunaga, Naoki; Yoshida, Kazuya; Kiribayashi, Seiga; Ohno, Kazunori; Takeuchi, Eijiro; Tadokoro, Satoshı; Akiyama, Hidehisa; Noda, Itsuki; Yoshida, Tomoaki; Koyanagi, Eiji

doi:10.1109/ssrr.2009.5424148

Cited by 10 publications

(4 citation statements)

References 10 publications

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“…In 2009, we entered Kenaf in the RoboCupRescue Robot League at Graz, Austria, to evaluate its performance on uneven terrain. In the competition, our team employed multiple robots, including Kenaf, which had fully autonomous systems (Nagatani et al, 2009). It used a navigator that determines the direction of travel and a subtrack controller with two LIDAR sensors.…”

Section: Methodsmentioning

confidence: 99%

Shared autonomy system for tracked vehicles on rough terrain based on continuous three‐dimensional terrain scanning

Okada

Nagatani

Yoshida

et al. 2011

Journal of Field Robotics

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Tracked vehicles are frequently used as search-and-rescue robots for exploring disaster areas. To enhance their ability to traverse rough terrain, some of these robots are equipped with swingable subtracks. However, manual control of such subtracks also increases the operator's workload, particularly in teleoperation with limited camera views. To eliminate this trade-off, we have developed a shared autonomy system using an autonomous controller for subtracks that is based on continuous three-dimensional terrain scanning. Using this system, the operator has only to specify the direction of travel to the robot, following which the robot traverses rough terrain using autonomously generated subtrack motions. In our system, real-time terrain slices near the robot are obtained using two or three LIDAR (laser imaging detection and ranging) sensors, and these terrain slices are integrated to generate three-dimensional terrain information. In this paper, we introduce an autonomous controller for subtracks and validate the reliability of a shared autonomy system on actual rough terrains through experimental results. C 2011 Wiley Periodicals, Inc. * Website: http://www.astro.mech.tohoku.ac.jp. tonomously travel to the location specified by the driver. Also, BigDog developed by Boston Dynamics (Raibert, Blankespoor, Nelson, & Playter, 2008) autonomously generates its leg motions to maintain stability and realize the desired direction of travel specified by the driver. Search-and-Rescue RobotsA number of research institutes are currently developing search-and-rescue robots for exploring disaster areas and obtaining information on victims during the initial stages of investigation (Tadokoro, Matsuno, & Jacoff, 2005). These robots are expected to support rescue operations and minimize the risk of injury to rescuers and victims from secondary disasters.It is extremely important for these robots to have high mobility over the rough terrains of disaster areas that are so often strewn with rubble; therefore, tracked vehicles are frequently used for such applications

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Section: Methodsmentioning

confidence: 99%

Shared autonomy system for tracked vehicles on rough terrain based on continuous three‐dimensional terrain scanning

Okada

Nagatani

Yoshida

et al. 2011

Journal of Field Robotics

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“…Most of the studies used the network capabilities in mobile robots and information sharing for coordination like in [8,9,10,11]. Researchers and developers studied the use of robots in different applications but the functionalities are still limited because of the need in storing large amount of information.…”

Section: Communicationmentioning

confidence: 99%

Information Sharing Model based on Adaptive Group Communication for Cloud-Enabled Robots

Mateo¹,

Lee²

2013

Journal of Korean Society for Internet Information

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In cloud robotics, the model to share information efficiently is still a research challenge. This paper presents an information sharing model for cloud-enabled robots to collaborate and share intelligence. To provide the efficient message dissemination, an adaptive group communication based on multi-agent is proposed. The proposed algorithm uses a weight function for the link nodes to determine the significant links. The performance evaluation showed that the proposed algorithm produced minimal message overhead and was faster to answer queries because of the significant links compared to traditional group communication methods.

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“…In recent years, due to the extensive application of multi-robotic networks in different categories, including path planning (Shen et al, 2019; Thabit and Mohades, 2019), evacuation (Zhang and Guo, 2015), search and rescue (Nagatani et al, 2009), cooperative localization (Chang and Mehta, 2018), object transportation (Barrientos et al, 2016) and formation control (Balch and Arkin, 1998), multi-robotic networks have received attention from researchers in related fields. Firstly, multiple robots dynamics have been described by model with different orders, nonholonomic chain model or Euler-Lagrange model (Du et al, 2016; Lu and Liu, 2019; Wang et al, 2009; Zhang et al, 2015), among which the most complicated model is the Euler-Lagrange model because of its strong nonlinearity.…”

Section: Introductionmentioning

confidence: 99%

Noise-tolerance consensus formation control for multi-robotic networks

Wang

et al. 2020

Transactions of the Institute of Measurement and Control

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This paper investigates the formation control for noise-tolerance consensus of multi-robotic networks and the mean square consensus condition. Firstly, the multi-robot model is expressed by applying a coordinate transformation based on the Euler-Lagrange equation. Compared with recent works, the control scheme presented in this work can indirectly obtain the evolution trend of position and velocity information of the robot. Besides, the noise and communication delay are involved in the formation control protocol. Secondly, the sufficient conditions of mean square consensus for formation control in multi-robotic networks with communication delay under noisy environments are obtained by using linear matrix inequality schemes. Finally, the numerical simulations are presented and submitted to demonstrate the correctness of the obtained results.

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Multi-robot exploration for search and rescue missions: A report of map building in RoboCupRescue 2009

Cited by 10 publications

References 10 publications

Shared autonomy system for tracked vehicles on rough terrain based on continuous three‐dimensional terrain scanning

Shared autonomy system for tracked vehicles on rough terrain based on continuous three‐dimensional terrain scanning

Information Sharing Model based on Adaptive Group Communication for Cloud-Enabled Robots

Noise-tolerance consensus formation control for multi-robotic networks

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