Fundamental development of a virtual reality simulator for four-arm disaster rescue robot OCTOPUS

Chen, Kui; Kamezaki, Mitsuhiro; Katano, Takahiro; Yang, Junjie; Ishida, Tatsuzo; Seki, Masatoshi; Ichiryu, Ken; Sugano, Shigeki

doi:10.1109/aim.2016.7576853

Cited by 8 publications

(1 citation statement)

References 12 publications

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“…Most of DRRs just specialize in one of them, but both of them are important in disaster response tasks. In order to improve performance of DRRs as well as enable them to be deployed to more complex disaster sites, we have developed hydraulic-driven OCTOPUS (h-OCTO-PUS), which has multi-DOF (degrees of freedom) four arms mounted on four sub-crawler robot [8,9]. We then developed electrically-driven OCTOPUS (e-OCTOPUS) for especially indoor applications, as shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Compound locomotion control system combining crawling and walking for multi-crawler multi-arm robot to adapt unstructured and unknown terrain

et al. 2018

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How to improve task performance and how to control a robot in extreme environments when just a few sensors can be used to obtain environmental information are two of the problems for disaster response robots (DRRs). Compared with conventional DRRs, multi-arm multi-flipper crawler type robot (MAMFR) have high mobility and task-execution capabilities. Because, crawler robots and quadruped robots have complementary advantages in locomotion, therefore we have the vision to combine both of these advantages in MAMFR. Usually, MAMFR (like four-arm four-flipper robot OCTOPUS) was designed for working in extreme environments such as that with heavy smoke and fog. Therefore it is a quite necessary requirement that DRR should have the ability to work in the situation even if vision and laser sensors are not available. To maximize terrains adaption ability, self-balancing capability, and obstacle getting over capability in unstructured disaster site, as well as reduce the difficulty of robot control, we proposed a semi-autonomous control system to realize this compound locomotion method for MAMFRs. In this control strategy, robot can explore the terrain and obtain basic information about the surrounding by its structure and internal sensors, such as encoder and inertial measurement unit. Except that control system also can recognize the relative positional relationship between robot and surrounding environment through its arms and crawlers state when robot moving. Because the control rules is simple but effective, and each part can adjust its own state automatically according to robot state and explored terrain, MRMFRs have better terrain adaptability and stability. Experimental results with a virtual reality simulator indicated that the designed control system significantly improved stability and mobility of robot in tasks, it also indicated that robot can adapt complex terrain when controlled by designed control system.

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Section: Introductionmentioning

confidence: 99%