An experiment in autonomous navigation of an underground mining vehicle

Abstract

Abstract-This paper describes the theoretical development and experimental evaluation of a navigation system for an autonomous load, haul, and dump truck (LHD) based on the results obtained during extensive in-situ field trials.1 The particular contributions of the theoretical work are in designing the navigation system to be able to cope with vehicle slip in rough uneven terrain using information from inertial sensors, odometry, and a bearing only laser. Results are presented using data obtained during the field trials.

A full error dynamics switching modeling and control scheme for an articulated vehicle

“…The cases that have been considered are the ones defined in (Table 1), while for each case a MPC has been tuned. The selected deviations for α and β have been inspired by a typical real life scenario slippage conditions and based on the analysis in [13,25], while the different parameter tuning for the utilized MPCs are being presented in Table 2. More analytically, in Fig.8, it is clearly presented that the proposed switching MPC has the merit of adapting to the varying articulated reference angle and achieve a good path tracking performance.…”

“…A control scheme that combines a kinematic controller and a sliding mode for wheeled mobile robots has been presented in [13,14]. In [15] a general kinematic model of an articulated vehicle has been proposed that described how heading angle evolved with time as a function of steering angle and velocity.…”

Automatic 3D Underground Mine Mapping

“…Early work by Shaffer [13] described a method to localize a mobile robot in an underground mine by registering terrain features (corner and line segments) extracted from an a priori survey map with cross-sections from an environment map produced by a laser scanner. In [11,12], Scheding extensively tested a set of navigation sensors mounted on a Load, Haul, and Dump truck (LHD) in the harsh underground mine environment. Using the data from a laser line scanner coupled with the navigation data of the vehicle, he produced a 3D model of a section of the mine.…”

Results in Combined Route Traversal and Collision Avoidance

“…There has been a great deal of attention paid to parts of the problem of autonomous operation in semi-structured environments such as in ports [6], underground mines [9], and highways [3]. In some of these cases, the environment can be controlled enough that obstacle detection can be simplified to ensuring that the machines are capable of stopping for people or vehicle sized obstacles.…”