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A Robotic Framework for the Robot@Factory 4.0 Competition

Robotic competitions stand as platforms to propel the forefront of robotics research while nurturing STEM education, serving as hubs of both applied research and scientific innovation. In Portugal, the Portuguese Robotics Open (FNR) is an event with several robotic competitions, including the Robot@Factory 4.0 competition. This competition presents an example of deploying autonomous robots on a factory shop floor. Thus, this framework intended for the Robot@Factory 4.0 competition is modular and open-access, enabling future participants to use and improve it in future editions. This work is the culmination of all the knowledge acquired by the 5dpo Robotics Team by winning the 2022 and 2023 editions of the competition.

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Sousa, R.B., Rocha, C.D., Martins, J.G., Costa, J.P., Padrão, J.T., Sarmento, J.M., Carvalho, J.P., Lopes, M.S., Costa, P.G., & Moreira, A.P. (2024). A Robotic Framework for the Robot@Factory 4.0 Competition. In: 2024 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), pp. 66-73. DOI: 10.1109/ICARSC61747.2024.10535935

Line Fitting-Based Corner-Like Detector for 2D Laser Scanners Data

The extraction of geometric information from the environment may be of interest to localisation and mapping algorithms. This feature extraction algorithm is intended to detect corner-like points in the 2D laser scan. The proposed methodology 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.

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Citation:

Sousa, R.B., Sobreira, H.M., Silva, M.F., & Moreira, A.P. (2024). Line Fitting-Based Corner-Like Detector for 2D Laser Scanners Data. In: 11th International Conference on Automation, Robotics, and Applications (ICARA), in press. DOI: N/A

OptiOdom: A Generic Approach for Odometry Calibration of Wheeled Mobile Robots

Odometry calibration adjusts the kinematic parameters or directly the robot's model to improve the wheeled odometry accuracy. The OptiOdom calibration algorithm, generalises the odometry calibration problem. It is developed an optimisation-based approach that uses the improved Resilient Propagation without weight-backtracking (iRprop-) for estimating the kinematic parameters using only the position data of the robot. Even though a calibration path is suggested to be used in the calibration procedure, the OptiOdom method is not path-specific. In the experiments performed, the OptiOdom was tested using four different robots on a square, arbitrary, and suggested calibration paths. The OptiTrack motion capture system was used as a ground-truth. Overall, the use of OptiOdom led to improvements in the odometry accuracy (in terms of maximum distance and absolute orientation errors over the path) over the existent literature while being a generalised approach to the odometry calibration problem. The OptiOdom and the methods from the literature implemented in the article are available in GitHub as an open-source repository.

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Citation:

Sousa, R.B., Petry, M.R., Costa, P.G., & Moreira, A.P. (2022). OptiOdom: a Generic Approach for Odometry Calibration of Wheeled Mobile Robots. Journal of Intelligent & Robotic Systems, 105(39). DOI: 10.1007/s10846-022-01630-3