移動候補に対する任意時点有効なターゲット保持を伴うマルチエージェント遅延決定軌道最適化
Multi-Agent Deferred-Decision Trajectory Optimization with Anytime-Valid Target Retention for Moving Candidates
複数の移動候補のうちどれが目標か不明な状況で、終端位置予測と逐次的候補棄却を組み合わせた遅延決定軌道最適化により、マルチエージェントで目標を捕捉する制御手法を提案した。
著者: Farbod Siahkali, Mengxue Hou, Vijay Gupta
分類: eess.SY, cs.LG, cs.RO
原文アブストラクト
We study multi-agent terminal interception when one of several moving candidates is the unknown target and both target identity and candidate terminal locations are uncertain. We develop a receding-horizon deferred-decision trajectory optimization (DDTO) controller that combines conformal terminal-location prediction, sequential candidate rejection, capacity-constrained assignment, and candidate-contingent planning. Under exchangeability conditions for terminal and identity residuals, with predictable querying, we establish fixed-time terminal-location coverage and anytime-valid target retention. At the final replan, when one control step remains, we bound the joint probability that a tightened-set DDTO plan passes nonlinear rollout verification but capture fails. The closed-loop controller applies fallback guidance to any agent without a verified DDTO plan and, across 100 paired scenarios, captures 79% of targets under the strict control-effort budget and 85% when that budget is relaxed.