We present a simultaneous sensor-based inspection and footprint coverage (SIFC) planning and control design with applications to autonomous robotic crack mapping and filling. The main challenge of the SIFC problem lies in the coupling of complete sensing (for mapping) and robotic footprint (for filling) coverage tasks. Initially, we assume known target information (e.g., crack) and employ classic cell decomposition methods to achieve complete sensing coverage of the workspace and complete robotic footprint coverage using the least-cost route. Subsequently, we generalize the algorithm to handle unknown target information, allowing the robot to scan and incrementally construct the target graph online while conducting robotic footprint coverage. The online polynomial-time SIFC planning algorithm minimizes the total robot traveling distance, guarantees complete sensing coverage of the entire workspace, and achieves near-optimal robotic footprint coverage, as demonstrated through empirical experiments. For the demonstrated application, we design coordinated nozzle motion control with the planned robot trajectory to efficiently fill all cracks within the robot's footprint. Experimental results are presented to illustrate the algorithm's design, performance, and comparisons. The SIFC algorithm offers a high-efficiency motion planning solution for various robotic applications requiring simultaneous sensing and actuation coverage.

翻译：我们提出了一种基于传感器的同步检测与足迹覆盖（SIFC）规划与控制设计方案，并应用于自主机器人裂纹映射与填充。SIFC问题的主要挑战在于完全感知（用于映射）与机器人足迹（用于填充）覆盖任务之间的耦合。初始阶段，我们假设已知目标信息（如裂纹），并采用经典单元分解方法，通过最低成本路径实现工作空间的完全感知覆盖以及机器人的完全足迹覆盖。随后，我们将算法推广至处理未知目标信息，允许机器人在执行足迹覆盖的同时，在线扫描并逐步构建目标图。在线多项式时间SIFC规划算法最小化机器人总行驶距离，保证整个工作空间的完全感知覆盖，并实现近最优的机器人足迹覆盖，这通过实证实验得到了验证。针对所展示的应用，我们设计了与规划轨迹协调的喷嘴运动控制，以在机器人足迹范围内高效填充所有裂纹。实验结果展示了算法的设计、性能及对比分析。SIFC算法为需要同步感知与执行覆盖的各类机器人应用提供了一种高效的运动规划解决方案。