A new Automation in Construction paper integrates RGB and depth sensing with grasp planning and robotic execution for construction and demolition waste. Its pipeline uses adaptive depth denoising, focal loss for sample imbalance, and a selection mechanism that suppresses redundant commands before action. The authors report 33 frames per second, a mean angle error of 2.64 degrees, 95.24% overall accuracy, and more than 97% recognition in robotic experiments. These are laboratory results, not proof of reliable operation amid every dust, occlusion, and material condition on a live demolition site.
A question for designCould an autonomous tool expose when it is suppressing an uncertain action, so throughput rises without hiding the limits of perception?*1