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29
Article The UspIC: Performing Scan Matching Localization Using an Imaging Sonar
, 2012
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Towards Model-Free SLAM Using a Single Laser Range Scanner for Helicopter MAV
"... A new solution for the SLAM problem is presented which makes use of a scan matching algorithm, and does not rely on bayesian filters. The virtual map is represented in the form of an occupancy grid, which stores laser scans based on the estimated position. The occupancy grid is scanned by means of r ..."
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A new solution for the SLAM problem is presented which makes use of a scan matching algorithm, and does not rely on bayesian filters. The virtual map is represented in the form of an occupancy grid, which stores laser scans based on the estimated position. The occupancy grid is scanned by means of ray casting to get a scan of the virtual world, called ”virtual scan”. The virtual scan therefore contains data from all previously acquired laser measurements and hence serves as the best representation of the surroundings. New laser scans are matched against the virtual scan to get an estimate of the new position. The scan matching cost function is minimized via an adaptive direct search with boundary updating until convergence. The resulting method is model-free and can be applied to various platforms, including micro aerial vehicles that lack dynamic models. Experimental validation of the SLAM method is presented by mapping a typical office hallway environment with a closed loop, using a manually driven platform and a laser range scanner. The mapping results are highly accurate and the loop closure area appears to be seamless, in spite of no loop closure algorithms and no post-mapping correction processes.
Experimental evaluation of a people detection algorithm in dynamic environments
- In ICRA
, 2009
"... Abstract—People detection is an important capability both for human-robot interaction in service robotics and to dis-tinguish the stable environment from the perturbation due to people motion in localization and mapping tasks. Several techniques have been proposed for different application contexts ..."
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Abstract—People detection is an important capability both for human-robot interaction in service robotics and to dis-tinguish the stable environment from the perturbation due to people motion in localization and mapping tasks. Several techniques have been proposed for different application contexts and sensors. Range data acquired by laser scanners are met-rically accurate and suitable for computationally-inexpensive people detection. Furthermore, laser scans provide a geometric description of local environment that can be combined with the information about dynamic objects. In this paper, a previously proposed method for detecting people legs from laser scans is experimentally evaluated and exploited to improve scan matching by removing dynamic parts corresponding to people. This algorithm splits laser scans into beam segments and classifies each segment. Classifications of simple features are then combined into a boosted classifier with Adaboost. The fundamental assumption of scan matching is that consecutive scans can be aligned with a rigid body transformation, since they represent the same scene. When dynamic elements like human legs are removed from scans, such assumption holds. We also investigate the effectiveness of the proposed people detection algorithm in terms of its ability to generalize across different environments and to support track persistency across scans. I.
Article Adaptive Covariance Estimation Method for LiDAR-Aided Multi-Sensor Integrated Navigation Systems
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A Scan Matching Method based on the Area Overlap of Star-Shaped Polygons
"... Abstract-We illustrate a method that performs scan matching by maximizing the intersection area of the scans. The intersection area is a robust parameter that is less prone to measurement errors with respect to alternative techniques. Furthermore, such technique does not require to associate each p ..."
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Abstract-We illustrate a method that performs scan matching by maximizing the intersection area of the scans. The intersection area is a robust parameter that is less prone to measurement errors with respect to alternative techniques. Furthermore, such technique does not require to associate each point of one scan to a point of the other one like in some popular algorithms. The relative pose that maximizes the overlap is estimated iteratively. Since the scans are represented by starshaped polygons due to visibility properties, their intersection can be computed using an efficient linear-time traversal of the vertices. Then, the relative pose is updated under the hypothesis that the combinatorics of intersection is left unchanged and the procedure is repeated until the scans are aligned with sufficient precision.
Matching Line Segment Scans with Mutual Compatibility Constraints
"... Abstract-Over the years, proposals have been made to employ line segments to build 2D maps of indoor environments. One of the basic steps of these approaches is the matching between scans (or, more generally, sets) of line segments, which is usually addressed using variants of the Iterative Closest ..."
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Abstract-Over the years, proposals have been made to employ line segments to build 2D maps of indoor environments. One of the basic steps of these approaches is the matching between scans (or, more generally, sets) of line segments, which is usually addressed using variants of the Iterative Closest Line (ICL) paradigm. ICL is based on the idea of associating closest line segments belonging to the two scans and of reducing the distance between them. In this paper, we propose two algorithms that go beyond this approach by exploiting the mutual compatibility between associations of line segments. Experimental results show that our algorithms significantly outperform, in terms of matching accuracy, traditional algorithms based on ICL, at the cost of a slightly longer execution time.
UNIVERSITY of CALIFORNIA Santa Barbara Distributed Coordination for Teams of Robots
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Loop Closure Transformation Estimation and Verification Using 2D LiDAR Scanners
"... Abstract — In many simultaneous localization and mapping (SLAM) systems, it is desirable to exploit the fact that the system is traversing though a previously visited environment. Once these locations, commonly known as loop closures, have been detected the system must be able to both compute and ve ..."
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Abstract — In many simultaneous localization and mapping (SLAM) systems, it is desirable to exploit the fact that the system is traversing though a previously visited environment. Once these locations, commonly known as loop closures, have been detected the system must be able to both compute and verify the relative transformation between proposed locations. In this paper we present two independent algorithms, using 2D LiDAR scanners, for robustly computing the transformation between arbitrary locations with overlapping geometry and validating the resulting transforms. First, a scan matching algorithm based on a genetic search and a fractional distance metric is presented. Secondly, two metrics are proposed to verify the recovered transforms. Through experimental results the proposed algorithms are shown to robustly estimate and validate loop closure transformations for both manually and automatically defined candidates. I.
Towards Obstacle Avoidance and Autonomous UAV Operation
"... This paper presents the status and progress of the ongoing work directed towards the development and implementation of autonomous navigation algorithms for Micro Aerial Vehicles (MAV). The method proposed is founded on a mapping methodology, which is supported by a laser scan matching algorithm and ..."
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This paper presents the status and progress of the ongoing work directed towards the development and implementation of autonomous navigation algorithms for Micro Aerial Vehicles (MAV). The method proposed is founded on a mapping methodology, which is supported by a laser scan matching algorithm and virtual occupancy grid method. Navigation and path planning is performed by means of an extended and optimized version of the potential field approach. This paper contains a description of the methodology along with initial results from both simulations and experiments that demonstrate the ability to navigate around corners from start to goal positions as well as mapping realistic corridor environments using a ground platform. A notable advantage of the current methodology is the separation between the MAV’s model and the navigation algorithm, which makes them suitable for various rotary wing (and other) platforms.
