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摘要: 复杂火灾场景下传统消防手段存在全局感知能力不足、协同能力弱等问题, 因此提出一种基于无人机空中引导的多消防机器人协同作业系统. 通过构建空−地异构协同架构, 融合无人机全局态势感知与地面消防机器人精准作业能力, 实现火灾动态环境下的高效协同灭火. 通过融合先验地图、高空侦察信息和多视角观测信息, 构建适用于灭火指控的多图层火场地图, 在保障关键信息获取的同时兼顾建图效率. 同时结合水柱轨迹模型、多视角观测信息及结构层数据, 实现水柱轨迹和落点的准确检测. 然后设计队列式与多形态主从编队模式, 配合快速队形重构算法生成编队参考信号. 进而, 基于提出的柔性预定性能函数设计无人机位姿矢量控制器, 以及基于改进视距导引法设计多消防机器人编队控制器. 最后, 开展空−地多机协同控制算法的仿真验证, 并将系统集成到开诚RXB-MC80BD消防机器人上进行应用测试.
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关键词:
- 多图层火场建图 /
- 柔性预定性能控制 /
- 无人机位姿矢量控制 /
- 消防机器人多模态编队
Abstract: Under complex fire scenarios, traditional firefighting methods suffer from limited global perception and weak collaboration capabilities. Therefore, a collaborative operation system with multiple firefighting robots guided by unmanned aerial vehicles (UAVs) is proposed. By establishing an air-ground heterogeneous collaborative architecture, the system integrates the global situational awareness of UAVs with the precise operation capabilities of ground firefighting robots, enabling efficient collaborative fire suppression in dynamic fire environments. By fusing prior maps, aerial reconnaissance information, and multi-view observations, a multi-layer fire scene map suitable for firefighting command and control is constructed, ensuring the acquisition of critical information while maintaining mapping efficiency. Combining the water jet trajectory model, multi-view observations, and structural layer data, the trajectory and landing point of the water jet are accurately detected. Furthermore, queue-based and multiform leader-follower formation configurations are designed, and formation reference signals are generated through a fast formation reconfiguration algorithm. Subsequently, a UAV pose-vector controller is developed by using the proposed flexible prescribed performance function, and a formation controller for multiple firefighting robots is designed based on an improved line-of-sight guidance method. Finally, the proposed air-ground multi-agent collaborative control algorithm is validated through simulations and implemented on the KaiCheng RXB-MC80BD firefighting robot platform for practical testing. -
图 3 不同柔性性能漏斗约束效果对比
Fig. 3 Comparison of different flexibility performance funnel constraint effects
图 2 综合约束下的无人机位姿轨迹
Fig. 2 Unmanned aerial vehicle pose trajectory under comprehensive constraints
图 4 偏航角的不同柔性预定性能约束对比
Fig. 4 Comparison of different flexible prescribed performance constraints for yaw angle
图 6 多消防机器人队列式编队轨迹图
Fig. 6 Queue-formation trajectory diagram of multiple firefighting robots
图 8 多消防机器人多形态编队轨迹图
Fig. 8 Multiform-formation trajectory diagram of multiple firefighting robots
表 1 无人机系统变量与矩阵定义
Table 1 Definition of system variables and matrices of UAVs
符号 表达式 说明 $m$ − 无人机质量 $I$ − 无人机转动惯量矩阵 ${{\boldsymbol{g}}}$ $[0,\; 0,\;-g]^{{\rm{T}}}$ 重力加速度向量 $J_{RP}$ − 旋翼电机组件的转动惯量 $ K_v$ ${\rm{diag}}\{k_x,\; k_y,\; k_z\}$ 线速度阻尼系数矩阵 $ K_\omega$ ${\rm{diag}}\{k_{\phi},\; k_{\theta},\; k_{\psi}\}$ 角速度阻尼系数矩阵 ${\boldsymbol{\Omega}}$ $[0,\; 0,\; \Omega]^{{\rm{T}}}$ 旋翼总转速向量 ${{\boldsymbol{f}}}_b$ $[0,\; 0,\; T]^{{\rm{T}}}$ 机体坐标系下总推力向量 ${\boldsymbol{\tau}}$ $[\tau_\phi,\; \tau_\theta,\; \tau_\psi]^{{\rm{T}}}$ 机体控制力矩向量 
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表 2 四旋翼仿真系统参数设置
Table 2 System parameter settings of quadrotor simulation
系统参数 符号 数值 无人机质量 $m$ 1.2 kg 转动惯量矩阵 $I$ ${\rm{diag}}\{0.01,\; 0.01,\; 0.02\}\; {\rm{kg}} \cdot {\rm{m}}^2$ 重力加速度 $g$ 9.81 m/s2 电机组件转动惯量 $J_{RP}$ 0.0001 kg·m2线速度阻尼系数 $ K_v$ ${\rm{diag}}\{0.1,\; 0.1,\; 0.2\}\;{\rm{N}} \cdot {\rm{s}}/{\mathrm{m}}$ 角速度阻尼系数 $ K_\omega$ ${\rm{diag}}\{0.05,\; 0.05,\; 0.05\}\;{\rm{N}} \cdot {\rm{m}} \cdot {\mathrm{s}}/{\mathrm{rad}}$ 旋翼臂长 $l$ 0.2 m 推力反扭矩系数 $\kappa$ 0.01 m 旋翼最大推力 $f_{\max}$ 10 N
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表 3 四旋翼仿真控制参数设置
Table 3 Control parameter settings of quadrotor simulation
控制参数 符号 数值 最大横滚角 $\phi_{\max}$ 0.26 rad 最大俯仰角 $\theta_{\max}$ 0.26 rad 位置误差预定性能 $\rho_p(t)$ $3 {\mathrm{e}}^{-0.5 t} + 0.1$ m 偏航角误差预定性能 $\rho_\psi(t)$ $3 {\mathrm{e}}^{-t} + 0.2$ rad 柔性边界参数 $\sigma$ 0.8 位置虚拟控制增益 $\Lambda_p$ ${\rm{diag}}\{1.0,\; 1.0,\; 1.2\}$ 速度误差增益 $\Lambda_v$ ${\rm{diag}}\{1.5,\; 1.5,\; 1.5\}$ 姿态误差增益 $\Lambda_\eta$ ${\rm{diag}}\{5.0,\; 5.0,\; 1.0\}$ 角速度误差增益 $\Lambda_\omega$ ${\rm{diag}}\{3.0,\; 3.0,\; 1.5\}$
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