Mining accidents have occurred since the early days of mining. Therewere a total of 525 mining disasters (incidents with five or more fatalities) in both coal and metal/nonmetal mines from 1900 through 2007 in the United States, resulting in 12,823 fatalities. Most of these disasters involve mine rescue teams, which are specially trained to perform search and rescue operations in extremely hostile environments. Robots have a great potential to assist in these underground operations, searching ahead of rescue teams and reporting conditions that may be hazardous to the teams. When explosive conditions exist or when heavy smoke or unstable ground conditions prevent team members from entering a mine, robots can become an invaluable tool.

Mobile robots in mine rescue and recovery

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Ground robotics in tunnels: Keys and lessons learned after 10 years of research and experiments

Method for the autonomous localization of a driverless, motorized vehicle within a known environment by using a range-measuring sensor which is arranged on the vehicle and in which the direction of measurement or plane of measurement can be altered by driving at least one sensor motor, wherein the method has the following steps: a map of the environment is produced by using natural landmarks; a predetermined route along which the vehicle is intended to move is stipulated; those landmarks which can serve as a localization aid along the predetermined route are determined; the environment is scanned at different times by using the sensor in order to detect the previously determined landmarks while the vehicle is moving along the predetermined route; and the vehicle is localized by comparing the detected landmarks with the landmarks recorded on the map; wherein the speed and/or the direction of rotation of the sensor motor is/are actively controlled, at least in areas of the environment with only a few previously determined landmarks, such that the sensor is oriented to these landmarks in order to ensure that they are detected.

Method for the autonomous localization of a driverless motorized vehicle

The master-followed multiple robots interactive cooperation simultaneous localization and mapping (SLAM) schemes were designed in this paper, which adapts to search and rescue (SAR) cluttered environments. In our multi-robots SLAM, the proposed algorithm estimates each of multiple robots’ current local sub-map, in this occasion, a particle represents each of moving multi-robots, and simultaneously, also represents the pose of a motion robot. The trajectory of the robot’s movement generated a local sub-map; the sub-maps can be looked on as the particles. Each robot efficiently forms a local sub-map; the global map integrates over these local sub-maps; identifying SAR objects of interest, in which, each of multi-robots acts as local-level features collector. Once the object of interest (OOI) is detected, the location in the global map could be determined by the SLAM. The designed multi-robot SLAM architecture consists of PC remote control center, a master robot, and multi-followed robots. Through mobileRobot platform, the master robot controls multi-robots team, the multiple robots exchange information with each other, and then performs SLAM tasks; the PC remote control center can monitor multi-robot SLAM process and provide directly control for multi-robots, which guarantee robots conducting safety in harsh SAR environments. This SLAM method has significantly improved the objects identification, area coverage rate and loop-closure, and the corresponding simulations and experiments validate the significant effects.

Master-followed Multiple Robots Cooperation SLAM Adapted to Search and Rescue Environment

This paper introduces a novel mobile robot design concept aimed at Exploration of subterranean spaces. The key innovation is the combination of highly maneuverable-body elements with wheel/leg elements (“whegs”). This combination offers performance not possible with conventional “monolithic” wheeled or tracked mobile robots, or with current robot snakes. The paper covers two design iterations of the concept, concentrating on describing the overall design process and results from initial tests.

Design, construction, and testing of a new class of mobile robots for cave exploration

This paper describes an autonomous platform for exploration and navigation within networks of tunnels, as those typically found in underground mines and caves. In this context, we propose a system allowing two modes of operation: exploration/surveying mode and autonomous navigation mode. In the exploration mode, a remotely located supervisor instructs the platform to move through successive sections of the network, gathering range data that is then concatenated into 2D/3D survey maps of the environment. In the navigation mode, the supervisor specifies high-level missions on the previously acquired survey maps. A motion planner then translates each mission into a set of consecutive navigation actions, separated by natural landmarks. Mission execution consists of autonomously detecting landmarks, self-localizing and performing the planned navigation actions. Advanced and innovative features, mostly related to exploration capabilities, navigation mode switcher, and the integrated aspect of our system distinguish it from the systems described in the literature.

J.N. Bakambu

Papers

Integrated Autonomous System for Exploration and Navigation in Underground Mines