Coxgraph: Multi-Robot Collaborative, Globally Consistent, Online Dense Reconstruction System

Real-time dense reconstruction has been extensively studied for its wide applications in computer vision and robotics, meanwhile much effort has been made for the multi-robot system which plays an irreplaceable role in complicated but time-critical scenarios, e. g. , search and rescue tasks. In this paper, we propose an efficient system named Coxgraph for multi-robot collaborative dense reconstruction in real-time. In our system, each client performs volumetric mapping in a producer-consumer manner. To facilitate transmission, we propose a compact 3D representation which transforms the SDF submap to mesh packs. During the recovery of submaps from mesh packs, the system can perform loop closure outlier rejection based on geometry consistency, trajectory collision and fitness check. Then we develop a robust map fusion method through joint optimization of trajectories and submaps. Extensive experiments demonstrate that our system can produce a globally consistent dense map in real-time with less transmission load, which is available as open-source software 1.

Authors

• Xiangyu Liu
• Weicai Ye
• Chaoran Tian
• Zhaopeng Cui
• Hujun Bao
• Guofeng Zhang 0001

Keywords

• Three-dimensional displays
• Collaboration
• Transforms
• Real-time systems
• Trajectory
• Time factors
• Multi-robot systems
• Global Consistency
• Dense Reconstruction
• Density Map
• Multi-agent Systems
• Compact Representation
• Computer Vision Applications
• Loop Closure
• Signed Distance Function
• Outlier Rejection
• Triangular
• Restaurants
• Free Space
• Global Optimization
• Point Cloud
• Path Planning
• Global Map
• Recovery Method
• Isosurface
• Reconstruction Results
• Surface Reconstruction
• Simultaneous Localization And Mapping
• Camera Pose
• Bandwidth Usage
• World Frame
• Visual Odometry
• Types Of Constraints
• Distribution Of Tasks
• Transmission Method
• Collaborative System