The construction industry faces productivity stagnation, skilled labor shortages, and safety concerns. While robotic automation offers solutions, construction robots struggle to adapt to unstructured, dynamic sites. Central to this is improvisation, adapting to unexpected situations through creative problem-solving, which remains predominantly human. In construction's unpredictable environments, collaborative human-robot improvisation is essential for workflow continuity. This research develops a six-level taxonomy classifying human-robot collaboration (HRC) based on improvisation capabilities. Through systematic review of 214 articles (2010-2025), we categorize construction robotics across: Manual Work (Level 0), Human-Controlled Execution (Level 1), Adaptive Manipulation (Level 2), Imitation Learning (Level 3), Human-in-Loop BIM Workflow (Level 4), Cloud-Based Knowledge Integration (Level 5), and True Collaborative Improvisation (Level 6). Analysis reveals current research concentrates at lower levels, with critical gaps in experiential learning and limited progression toward collaborative improvisation. A five-dimensional radar framework illustrates progressive evolution of Planning, Cognitive Role, Physical Execution, Learning Capability, and Improvisation, demonstrating how complementary human-robot capabilities create team performance exceeding individual contributions. The research identifies three fundamental barriers: technical limitations in grounding and dialogic reasoning, conceptual gaps between human improvisation and robotics research, and methodological challenges. We recommend future research emphasizing improved human-robot communication via Augmented/Virtual Reality interfaces, large language model integration, and cloud-based knowledge systems to advance toward true collaborative improvisation.

翻译：建筑业面临生产力停滞、熟练劳动力短缺及安全隐患等问题。机器人自动化虽提供解决方案，但建造机器人在适应非结构化动态工地时仍存在困难。其核心在于即兴能力——通过创造性问题解决适应意外情境的能力，这目前仍主要依赖人类。在建造业不可预测的环境中，人机协同即兴对于工作流连续性至关重要。本研究构建了一个基于即兴能力的六级分类体系，对人机协作进行系统划分。通过对214篇文献（2010-2025年）的系统综述，我们将建造机器人技术划分为：人工操作（0级）、人控执行（1级）、自适应操控（2级）、模仿学习（3级）、人在环BIM工作流（4级）、云端知识集成（5级）及真协同即兴（6级）。分析表明当前研究集中于较低层级，在经验学习方面存在显著空白，向协同即兴的演进有限。我们提出五维雷达框架，从规划、认知角色、物理执行、学习能力与即兴性五个维度展示渐进演化路径，论证了互补性人机能力如何创造超越个体贡献的团队效能。研究识别出三大根本障碍：具身认知与对话推理的技术局限、人类即兴行为与机器人研究间的概念鸿沟，以及方法论挑战。建议未来研究应着重通过增强/虚拟现实界面、大语言模型集成及云端知识系统来改进人机通信，以推动实现真正的协同即兴。