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This paper describes an autonomous platform for navigation and surveying 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: surveying and autonomous navigation mode. In the surveying mode, a remotely located supervisor instructs the platform to move through successive sections of the network, gathering range data that is then concatenated into two‐ and three‐dimensional survey maps of the environment. In navigation mode, the supervisor specifies high‐level missions using 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 surveying capabilities, navigation mode switcher, and the integrated aspect of our system, distinguish it from navigation systems used in productive mining vehicles described in the literature. The proposed system starts sharing some functionality with robotics systems devoted to exploration of abandoned mines. The full functionality of the navigation/surveying system has been proven through a series of on‐site experiments in underground mines. © 2007 Wiley Periodicals, Inc.

A path tracking control algorithm for tracked surface drilling machines is presented. The general dynamic model of such vehicle is simulated including track-soil interactions. The controller is based on feedback linearization of the equations with feedforward fraction compensation. I t linearizes the complex forceslip relationship to relate the states of the system to the inputs. The controller based on simplified models is applied to the detailed simulated model of the vehicle. The result is an accurate control of the lateral offset and forward velocity error along a path.

Obsiacles detection is essential to safe autonomous platjionn navigation. The obstacle detection methods proposed in the literature do not pay suflcient attention to the occlusion-problem caused by the existence of regions along the trajectory of a vehicle that are hidden by other objects and where potential obstacles might be located. Our approach takes occlusions into account to preveni-the possibility of collision. Experimental results with a robotic platjiomz demonstrating the effectiveness of the developed algorithm are presented.

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