Pancham, ArdhishaWithey, Daniel JBright, G2018-05-182018-05-182018-03Pancham, A., Withey, D.J. and Bright, G. 2018. Evaluation of a simultaneous localization and mapping algorithm in a dynamic environment using a red green blue - depth camera. In: Dash S., Naidu P., Bayindir R., Das S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 668. Springer, Singapore978-981-10-7867-5978-981-10-7868-2https://link.springer.com/chapter/10.1007/978-981-10-7868-2_68https://doi.org/10.1007/978-981-10-7868-2_68http://hdl.handle.net/10204/10217Copyright: 2018 Springer. Due to copyright restrictions, the attached PDF file contains the accepted version of the published paper. For access to the published paper, please consult the publisher's website.Simultaneous Localization And Mapping (SLAM) assumes a static environment. In a dynamic environment, the localization accuracy and map quality of SLAM may be degraded by moving objects. By removing these moving objects SLAM performance may improve. Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features) (ORB)-SLAM is a state-of-the-art SLAM algorithm that has shown good performance on several Red Green Blue - Depth (RGB-D) datasets with a moving camera in static and dynamic environments. ORB-SLAM is robust to moderate dynamic changes. However, ORB-SLAM has not been evaluated with a moving RGB-D camera and an object moving at a range of specific linear speeds. This paper evaluates the performance of ORB-SLAM with a moving RGB-D camera in a dynamic environment that includes an object moving at a range of specific linear speeds. Results from experiments indicate that a moving object at lower speeds, in the range tested, degrades the performance of ORB-SLAM and by removing the moving object the performance of ORB-SLAM improves.enORB-SLAMSLAMIDESLAMDynamic environmentRGB-D cameraConference PresentationPancham, A., Withey, D. J., & Bright, G. (2018). Evaluation of a simultaneous localization and mapping algorithm in a dynamic environment using a red green blue - depth camera. Springer. http://hdl.handle.net/10204/10217Pancham, Ardhisha, Daniel J Withey, and G Bright. "Evaluation of a simultaneous localization and mapping algorithm in a dynamic environment using a red green blue - depth camera." (2018): http://hdl.handle.net/10204/10217Pancham A, Withey DJ, Bright G, Evaluation of a simultaneous localization and mapping algorithm in a dynamic environment using a red green blue - depth camera; Springer; 2018. http://hdl.handle.net/10204/10217 .TY - Conference Presentation AU - Pancham, Ardhisha AU - Withey, Daniel J AU - Bright, G AB - Simultaneous Localization And Mapping (SLAM) assumes a static environment. In a dynamic environment, the localization accuracy and map quality of SLAM may be degraded by moving objects. By removing these moving objects SLAM performance may improve. Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features) (ORB)-SLAM is a state-of-the-art SLAM algorithm that has shown good performance on several Red Green Blue - Depth (RGB-D) datasets with a moving camera in static and dynamic environments. ORB-SLAM is robust to moderate dynamic changes. However, ORB-SLAM has not been evaluated with a moving RGB-D camera and an object moving at a range of specific linear speeds. This paper evaluates the performance of ORB-SLAM with a moving RGB-D camera in a dynamic environment that includes an object moving at a range of specific linear speeds. Results from experiments indicate that a moving object at lower speeds, in the range tested, degrades the performance of ORB-SLAM and by removing the moving object the performance of ORB-SLAM improves. DA - 2018-03 DB - ResearchSpace DP - CSIR KW - ORB-SLAM KW - SLAMIDE KW - SLAM KW - Dynamic environment KW - RGB-D camera LK - https://researchspace.csir.co.za PY - 2018 SM - 978-981-10-7867-5 SM - 978-981-10-7868-2 T1 - Evaluation of a simultaneous localization and mapping algorithm in a dynamic environment using a red green blue - depth camera TI - Evaluation of a simultaneous localization and mapping algorithm in a dynamic environment using a red green blue - depth camera UR - http://hdl.handle.net/10204/10217 ER -