Manipulation

Insertion Task

An insertion task is the class of manipulation problems requiring one part to be fitted into another under tight clearances, with peg-in-hole as the canonical example and connector mating, gear meshing, and furniture assembly as practical variants. Success under sub-millimeter tolerances demands exploiting contact through compliance, force feedback, or learned search strategies, and benchmarks such as the NIST Assembly Task Boards standardize evaluation.

Why it matters for physical AI

Insertion dominates electronics assembly and manufacturing work, and because vision alone rarely achieves the required precision, it is the proving ground for force-aware and contact-rich learned policies.