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Article

Development of Sensing Algorithms for Object Tracking and Predictive Safety Evaluation of Autonomous Excavators

1
Department of Automotive and Mechatronics Engineering, Ontario Tech University, Oshawa, ON L1G 0C5, Canada
2
Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
*
Author to whom correspondence should be addressed.
Academic Editor: Sungho Kim
Appl. Sci. 2021, 11(14), 6366; https://doi.org/10.3390/app11146366
Received: 28 April 2021 / Revised: 2 July 2021 / Accepted: 6 July 2021 / Published: 9 July 2021
This article presents the sensing and safety algorithms for autonomous excavators operating on construction sites. Safety is a key concern for autonomous construction to reduce collisions and machinery damage. Taking this point into consideration, our study deals with LiDAR data processing that allows for object detection, motion tracking/prediction, and track management, as well as safety evaluation in terms of potential collision risk. In the safety algorithm developed in this study, potential collision risks can be evaluated based on information from excavator working areas, predicted states of detected objects, and calculated safety indices. Experiments were performed using a modified mini hydraulic excavator with Velodyne VLP-16 LiDAR. Experimental validations prove that the developed algorithms are capable of tracking objects, predicting their future states, and assessing the degree of collision risks with respect to distance and time. Hence, the proposed algorithms can be applied to diverse autonomous machines for safety enhancement. View Full-Text
Keywords: autonomous excavation; construction safety; IMM-UK-JPDA; excavator working area; LiDAR; motion prediction; object tracking; safety evaluation autonomous excavation; construction safety; IMM-UK-JPDA; excavator working area; LiDAR; motion prediction; object tracking; safety evaluation
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MDPI and ACS Style

Rasul, A.; Seo, J.; Khajepour, A. Development of Sensing Algorithms for Object Tracking and Predictive Safety Evaluation of Autonomous Excavators. Appl. Sci. 2021, 11, 6366. https://doi.org/10.3390/app11146366

AMA Style

Rasul A, Seo J, Khajepour A. Development of Sensing Algorithms for Object Tracking and Predictive Safety Evaluation of Autonomous Excavators. Applied Sciences. 2021; 11(14):6366. https://doi.org/10.3390/app11146366

Chicago/Turabian Style

Rasul, Abdullah, Jaho Seo, and Amir Khajepour. 2021. "Development of Sensing Algorithms for Object Tracking and Predictive Safety Evaluation of Autonomous Excavators" Applied Sciences 11, no. 14: 6366. https://doi.org/10.3390/app11146366

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