Vechev, VelkoZarate, JuanThomaszewski, BernhardHilliges, OtmarChaine, RaphaëlleKim, Min H.2022-04-222022-04-2220221467-8659https://doi.org/10.1111/cgf.14492https://diglib.eg.org:443/handle/10.1111/cgf14492Kinesthetic garments provide physical feedback on body posture and motion through tailored distributions of reinforced material. Their ability to selectively stiffen a garment's response to specific motions makes them appealing for rehabilitation, sports, robotics, and many other application fields. However, finding designs that distribute a given amount of reinforcement material to maximally stiffen the response to specified motions is a challenging problem. In this work, we propose an optimization-driven approach for automated design of reinforcement patterns for kinesthetic garments. Our main contribution is to cast this design task as an on-body topology optimization problem. Our method allows designers to explore a continuous range of designs corresponding to various amounts of reinforcement coverage. Our model captures both tight contact and lift-off separation between cloth and body. We demonstrate our method on a variety of reinforcement design problems for different body sites and motions. Optimal designs lead to a two- to threefold improvement in performance in terms of energy density. A set of manufactured designs were consistently rated as providing more resistance than baselines in a comparative user study.CCS Concepts: Applied computing --> Computer-aided manufacturing; Computing methodologies --> Physical simulationApplied computingComputeraided manufacturingComputing methodologiesPhysical simulation10.1111/cgf.14492535-54612 pages