#artificial intelligence
Jun 2026
Transformer-Based Warm-Starting for Feasible and Optimal Terminal Approach to Tumbling Objects with Space Manipulators
A causal-transformer warm-start for the computationally dominant attitude-manipulator stage of a two-stage sequential convex programming (SCP) framework is developed and demonstrated that learned warm-starts can reduce onboard optimization cost while steering SCP toward basins containing feasible, low-cost solutions.
Yuji Takubo, M. Adang, Mac Schwager et al.
· arXiv.org · 2 citations