HEAPGrasp, Swarm AGVs, and the Push to Handle Any Object at Scale

Research

HEAPGrasp Achieves 96% Grasping Success on Transparent and Reflective Objects Using Only RGB Camera

Tokyo University of Science's HEAPGrasp system sidesteps the classic depth-sensor failure mode for glass and shiny objects by relying purely on silhouettes from standard RGB images. It also cuts camera travel distance by 52% and execution time by 19%, which makes it practical to retrofit onto existing lines without new hardware investments.

News

Toyota Launches Swarm Automation Transport System for Mixed-Fleet Warehouse Logistics

Toyota's Swarm system pairs its SAI125CB automated stacker with T-ONE software to coordinate automated and manual fleets handling multiple pallet formats. The ability to start hybrid and scale up incrementally lowers the barrier to entry for warehouses not ready to go fully automated overnight.

Analysis

How Shape from Silhouette Makes Robots Stop Fumbling with Glass and Metal Parts

This breakdown explains the core SfS technique behind HEAPGrasp and why it is inherently more robust than depth-based approaches for optically tricky materials. Worth reading if you are evaluating vision systems for any environment that mixes transparent trays, shiny parts, or specular packaging.