Volcano robots

Summary of MUAV-based volcano observation system

When a volcano erupts, molten rocks, ash, pyroclastic flow, and debris flow can cause disasters. Debris flow is responsible for enormous damage across large areas. This makes debris flow simulations a crucial means of determining whether to issue an evacuation warning for area residents. For safety purposes, restricted areas are designated around volcanos during eruptions, making it difficult to gather information (such as the amount and permeability of ash) required for precise debris flow simulations. An unmanned observation system, intended for use in such restricted areas, was developed to address this issue. The proposed system is based on a multirotor micro-unmanned aerial vehicle (MUAV) that transports cameras, small devices to measure target environments, and a small robot to active volcanic areas. Field experiments were conducted at Mt. Asama and Mt. Unzen-Fugen to validate the function of the system. Data obtained by these systems can contribute to the improvement of debris flow simulations developed in the project.


Development of Multi DOF Tracked Vehicle to Improve weak slope terrainability

In response to active volcano observation, our research group developed a novel multi-D.O.F. tracked vehicle, called ELF. The robot essentially consists of six tracks, and it has eleven actuators for locomotion and change of configuration. These actuators enable the robot to assume various configurations, which increase its ability to traverse weak and rough terrains in volcanic areas. In this movie-clip, the mechanism of Elf and its initial test in a volcanic field are introduced.


Autonomous Lake Bed Depth Mapping by a Portable Semi-submersible USV at Mt. Zao Okama Crater Lake

Surveillance of the crater lake is valuable for volcanic disaster prevention. However, this is dangerous work for humans. We developed an autonomous depth mapping system to reduce the risk of surveillance. A field test was performed at Mt. Zao Okama Crater Lake on June 2, 2016. The path for the autonomous depth mapping was designed to avoid manned surveillance. The navigation through 450 meters of the path was done in 35 minutes. No upset occurs under 5 to 20 m/s of winds and blast. A maximum angle of the body swing was 0.09 rad. Lake bed depth map was successfully generated by the autonomous USV system.


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