CRIIS - Indexed Articles in Conferences

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    Evolution of Odometry Calibration Methods for Ground Mobile Robots
    ( 2020) António Paulo Moreira ; Marcelo Petry ; Ricardo Barbosa Sousa ; 5157 ; 5240 ; 7908
    Localisation is a critical problem in ground mobile robots. For dead reckoning, odometry is usually used. A disadvantage of using it alone is unbounded error accumulation. So, odometry calibration is critical in reducing error propagation. This paper presents an analysis of the developments and advances of systematic methods for odometry calibration. Four steering geometries were analysed, namely differential drive, Ackerman, tricycle and omnidirectional. It highlights the advances made on this field and covers the methods since UMBmark was proposed. The points of analysis are the techniques and test paths used, errors considered in calibration, and experiments made to validate each method. It was obtained fifteen methods for differential drive, three for Ackerman, two for tricycle, and three for the omnidirectional steering geometry. A disparity was noted, compared with the real utilisation, between the number of published works addressing differential drive and tricycle/Ackerman. Still, odometry continues evolving since UMBmark was proposed.
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    Extrinsic sensor calibration methods for mobile robots: A short review
    ( 2021) António Paulo Moreira ; Marcelo Petry ; Ricardo Barbosa Sousa ; 5157 ; 5240 ; 7908
    Data acquisition is a critical task for localisation and perception of mobile robots. It is necessary to compute the relative pose between onboard sensors to process the data in a common frame. Thus, extrinsic calibration computes the sensor’s relative pose improving data consistency between them. This paper performs a literature review on extrinsic sensor calibration methods prioritising the most recent ones. The sensors types considered were laser scanners, cameras and IMUs. It was found methods for robot–laser, laser–laser, laser–camera, robot–camera, camera–camera, camera–IMU, IMU–IMU and laser–IMU calibration. The analysed methods allow the full calibration of a sensory system composed of lasers, cameras and IMUs. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.
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    A Pose Control Algorithm for Omnidirectional Robots
    ( 2021) António Paulo Moreira ; Ricardo Barbosa Sousa ; 5157 ; 7908
    The pose control (position and orientation) of a robot is important to control how and when the robot gets to the desired pose at the desired time in order to perform some task. Controlling omnidirectional robots is of great interest due to their complete maneuverability. So, we use Proportional-Integrative (PI), Proportional-Derivative (PD), and Feed-Forward (FF) controllers to control the pose of an omnidirectional robot in space and in time. The proposed controller approximates the future trajectory (a subset of points) on parametric polynomials for computing the derivatives needed in the FF. In the simulations performed, it was analyzed the size of the future trajectory horizon for the controller depending on the robot's velocity, and the proposed controller was compared to PD-only and a generic GoToXY controller. The results demonstrated that the proposed controller achieves better results than the other two both in space and in time.
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    Line Fitting-Based Corner-Like Detector for 2D Laser Scanners Data
    ( 2024) Ricardo Barbosa Sousa ; Manuel Santos Silva ; António Paulo Moreira ; 7908 ; 5655 ; 5157
    The extraction of geometric information from the environment may be of interest to localisation and mapping algorithms. Existent literature on extracting geometric features from 2D laser data focuses mainly on detecting lines. Regarding corners, most methodologies use the intersection of line segment features. This paper presents a feature extraction algorithm for corner-like points in the 2D laser scan. The proposed methodol-ogy defines arrival and departure neighbourhoods around each scan point and performs local line fitting evaluated in multiple distance-based scales. Then, a set of indicators based on line fitting error, the angle between arrival and departure lines, and consecutive observation of the same keypoint across different scales determine the existence of a corner-like feature. The experiments evaluated the corner-like features regarding their relative position and observability, achieving standard deviations on the relative position lower than the sensor noise and visibility ratios higher than 75% with very low false positives rates. © 2024 IEEE.