Vision-based robotic system for on-site construction and demolition waste sorting and recycling

Construction and demolition waste (CDW) causes severe pollution on a global scale, as we can see from western countries' as well as Chinese statistics. CDW accounts over 25% of Hong Kong's solid waste and about 40% for Australia and EU. The classification and recycling of CDW on construction sites make a vital contribution to the successful recycling of CDW. Currently, recycling of onsite construction waste is very time consuming and labor-intensive, which is probably one of the most critical reasons for inefficient CDW management. Previous experiences found that computer vision performed well in CDW recycling, but in special cases, the accuracy of the patrol and the picking method may cause failure. To reduce the occurrence of failure, this research adopts the Simultaneous Localization and Mapping (SLAM) technology and the instance segmentation method to enable the robot to cope with complex site situations. A database of CDW was developed and used to train a computer vision model for recognizing residual pipes and cables. The feasibility of developed methods and algorithms was evaluated through both lab and site experiments. The system can be improved and applied to other objects, which is useful for researchers and practitioners engaged in similar tasks.