A Kalman-filtering-based Approach for Improving Terrain Mapping in off-road Autonomous Vehicles

Abstract

Artículo de publicación ISIThe generation of accurate terrain maps while navigating over off-road, irregular terrains is a complex challenge, due to the difficulties in the estimation of the pose of the laser rangefinders, which is required for the proper registration of the range measurements. This paper addresses this problem. The proposed methodology uses an Extended Kalman filter to estimate in real-time the instantaneous pose of the vehicle and the laser rangefinders by considering measurements acquired from an inertial measurement unit, internal sensorial data of the vehicle and the estimated heights of the four wheels, which are obtained from the terrain map and allow determination of the vehicle's inclination. The estimated 6D pose of the laser rangefinders is used to correctly project the laser measurements onto the terrain map. The terrain map is a 2.5D map that stores in each cell the mean value and variance of the terrain height. In each map's cell position, new laser observations are fused with existing height estimations using a Kalman filter. The proposed methodology is validated in the real world using an autonomous vehicle. Field trials show that the use of the proposed state estimation methodology produces maps with much higher accuracy than the standard approaches.FONDECYT 113015

Toward Autonomous Vehicles and Machinery in Mill Yards of the Forest Industry: Technologies and Proposals for Autonomous Vehicle Operations

“…Localization 9 Global navigation satellite systems [18], [53] Simultaneous localization and mapping [52], [54], [55], [56] A priori map-based localization [57], [58], [50] Perception 16 Object detection and classification [60], [47], [48], [63] Road and obstacle detection [64], [65], [66], [68] [69], [70], [71], [72], [73], [47], [55], [49] Control & task execution [74], [75] 2…”

“…It was noted, however, that the outdoor environment was much more challenging due to the uneven ground and changing soil types. A system specifically developed for off-road mapping and localization is described in [56]. The system can produce accurate terrain mapping while navigating in an off-road environment.…”

Robotics research in Chile

“…More details on the control modules used in this vehicle can be found in the literature. 8,9 Some of the main methods and algorithms that have been developed using this autonomous vehicle are as follows:…”

“…An adaptive and real-time visual road segmentation method for off-road autonomous driving 8 : The method is based on the use of adaptive color histograms; however, its main novelties are the use of the random sample consensus algorithm 10 in order to determine the road borders and the vanishing point and a set of heuristic rules that allow checking the spatiotemporal consistency of the road determination. A Kalman-filtering-based approach for improving terrain mapping in off-road autonomous driving applications 9 : The proposed methodology uses an extended Kalman filter 11 to estimate in real time the instantaneous pose of the vehicle and the laser range finders by considering measurements acquired from an inertial measurement unit, internal sensorial data of the vehicle, and the estimated heights of the four wheels, which are obtained from the terrain map, and allow determination of the vehicle's inclination. The estimated 6D pose of the laser range finders is used to correctly project the laser measurements onto the terrain map.…”