# 信念引导的混合控制及几乎必然目标集收敛

> 原文链接：https://robotics.hellobike.com/papers/2026-10-06-2610-07674
> 频道：papers | 更新日期：2026-10-06 | 标签：arxiv, cs.RO
> 核心摘要：针对参数不确定下混合系统到达目标集，提出信念信息双控制算法，并在平面调节和仿真双臂装配中验证。

# 信念引导的混合控制及几乎必然目标集收敛

::: v-pre
> 原文链接：[Belief-Informed Hybrid Control with Almost-Sure Target-Set Convergence](https://arxiv.org/abs/2610.07674)（arXiv 2610.07674 · 发布日期：2026-10-06）

**Belief-Informed Hybrid Control with Almost-Sure Target-Set Convergence**

针对参数不确定下混合系统到达目标集，提出信念信息双控制算法，并在平面调节和仿真双臂装配中验证。

## 核心要点

- 参数不确定时，获取信息的动作可能需暂时远离目标集。
- 算法结合信念空间滚动时域选择、期望下降约束和松弛状态。
- 两步前瞻用预测观测更新信念，并给出几乎必然收敛证明。
- 平面调节11步内降至0.01，仿真装配误差较基线低96.4%。

**验证范围与局限**：验证范围为平面调节与仿真双臂装配，摘要未报告真机实验。

## 英文摘要 (Abstract)

Controlling a hybrid system to a target set under parameter uncertainty can require informative actions that temporarily drive the system state away from the specified set. We propose a belief-informed dual-control algorithm that combines belief-space receding-horizon selection with an expected-decrease constraint on a nonnegative target-set progress function. To accommodate exploratory deviations, a scalar controller state bounds the constraint's cumulative slack. Our algorithm's two-step lookahead selection uses predicted observations to update the parameter belief before evaluating the subsequent action's admissibility. Under distance-comparison bounds, correct conditional prediction, and recursive feasibility, we prove almost-sure target-set convergence at decision times and bound both the sum of expected progress-function values and the expected neighborhood-entry time. Upper confidence bounds extend these convergence guarantees to bounded model samples with summable error probabilities. In planar regulation with an unknown control direction, we verify recursive feasibility: the proposed two-step selection reduces the Euclidean state norm below 0.01 within 11 decisions for either sign, whereas a myopic one-step selection loses admissibility immediately after zero input. In a simulated bimanual assembly task, our algorithm's one-step implementation uses clearance feedback to complete the assembly under nominal friction, yielding a 96.4% lower infinity-norm relative-position error than the reference-tracking baseline at the method's completion time. At lower friction, its posterior conditioning successfully detects an empty admissible set, whereas a fixed-prior alternative admits an action that violates the conditional decrease constraint. Project page: https://clintonenwerem.com/belief-hybrid-control/.

作者：Clinton O. Enwerem, Saleh Kemal, John S. Baras, Calin A. Belta
:::

## 原始参考来源 (Sources)

- [arXiv 2610.07674：Belief-Informed Hybrid Control with Almost-Sure Target-Set Convergence](https://arxiv.org/abs/2610.07674)