This paper describes the outcomes of the Forecast project, aiming at providing tools and metrics to benchmark force control algorithms for robotics applications. The Forecast project recognizes the importance of considering the interacting environment in order to assess the performance of a force-controlled system. In many papers, force-controlled systems are often evaluated on too specific (and often favorable) environmental conditions, preventing readers from fairly understanding the overall system behavior. Starting from these observations, the Forecast project has developed tools and metrics to ease and standardize the benchmarking process. The objective of this paper is to present such tools and metrics and to foster their diffusion within the robotics community. A case study is proposed to practically showcase the benchmarking process.
The ForceCAST framework: Methodology and tools for benchmarking force control algorithms
Dimo, Eldison;Meneghetti, Matteo;Calanca, Andrea
2026-01-01
Abstract
This paper describes the outcomes of the Forecast project, aiming at providing tools and metrics to benchmark force control algorithms for robotics applications. The Forecast project recognizes the importance of considering the interacting environment in order to assess the performance of a force-controlled system. In many papers, force-controlled systems are often evaluated on too specific (and often favorable) environmental conditions, preventing readers from fairly understanding the overall system behavior. Starting from these observations, the Forecast project has developed tools and metrics to ease and standardize the benchmarking process. The objective of this paper is to present such tools and metrics and to foster their diffusion within the robotics community. A case study is proposed to practically showcase the benchmarking process.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



