2025
Task-Parameterized Motion Learning With Time-Sensitive Constraints
RA-L 2025
Teaching motion skills to robots through demonstrations has becomes widely popular. However, precise execution of start-, via-, and end-poses at given times is often not guaranteed, limiting the technology transfer to industrial application. To address this issue, we propose the novel <italic xmlns: