Fast In-situ Mesh Generation using Orb-SLAM2 and OpenMVS

Thomas Wright, Toshihide Hanari, Kuniaki Kawabata, Barry Lennox

Research output: Contribution to conferencePaperpeer-review


In exploratory robotics for nuclear decommissioning, environmental understanding is key. Sites such as Fukushima Daiichi Power Station and Sellafield often use manually controlled or semi-autonomous vehicles for exploration and monitoring of assets. In many cases, robots have limited sensing capabilities such as a single camera to provide video to the operators. These limitations can cause issues, where a lack of data about the environment and limited understanding of depth within the image can lead to a mis-understanding of asset state or potential damage being caused to the robot or environment. This work aims to aid operators by using the limited sensors provided i.e. a single monocular camera, to allow estimates of the robot's surrounding environments to be generated insitu without having to off load large amounts of data for processing. This information can then be displayed as a mesh and manipulated in 3D to improve the operator awareness. Due to the target environment for operation being radioactive, speed is prioritised over accuracy, due to the damaging effects radiation can cause to electronics. In well lit environments images can be overlaid onto the meshes to improve the operators understanding and add detail to the mesh. From the results it has been found that 3D meshes of an environment/object can be generated in an acceptable time frame, less than 5 minutes. This differs from many current methods which require offline processing due to heavy computational requirement of Photogrammetry, or are far less informative giving data as raw point clouds, which can be hard to interpret. The proposed technique allows for lower resolution meshes good enough for avoiding collisions within an environment to be generated during a mission due to it's speed of generation, however there are still several issues which need to be solved before such a technique is ready for deployment.
Original languageEnglish
Number of pages7
Publication statusPublished - 21 Jul 2020
Event2020 17th International Conference on Ubiquitous Robots (UR) -
Duration: 22 Jun 202026 Jun 2020


Conference2020 17th International Conference on Ubiquitous Robots (UR)
Abbreviated titleUR


  • Robotics
  • Computer vision
  • SLAM
  • Nuclear waste


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