用大模型和知识图谱让机器人更懂指令，自动分解任务并规避风险。
ConceptBot: Enhancing Robot's Autonomy through Task Decomposition with Large Language Models and Knowledge Graph
- 融合大模型与知识图谱，从自然语言中提取物体属性并解析任务意图。
- 在隐含指令、风险任务等挑战下成功率超SayCan，最高达100%且风险识别准确率76%。
- 适合需要自主决策的复杂场景，如物品分类与毒性检测，无需领域训练。
ConceptBot是一种模块化机器人规划框架，结合大型语言模型与知识图谱，在自然语言指令模糊及环境物体识别困难的情况下，仍能生成可行且具备风险意识的计划，克服了常识推理不足的问题。该框架包含三个核心模块：(i) 物体属性提取（OPE）模块，利用ConceptNet语义概念增强场景理解；(ii) 用户请求处理（URP）模块，消歧并结构化指令；(iii) 规划器，生成上下文感知、可执行的拾取-放置策略。在对比实验中，ConceptBot在显式任务上实现100%成功率，隐含任务准确率达87%（远超SayCan的31%），风险感知任务成功率达76%（对比仅15%），并在特定场景中表现优异，如材料分类（70% vs. 20%）、毒性检测（86% vs. 36%）。在SafeAgentBench评测中总得分为80%（次优基线为46%）。实验结果在仿真与实验室环境中均验证，表明其无需领域特定训练即可泛化，显著提升非结构化环境下机器人策略的可靠性。
原文摘要 · Abstract (English)
ConceptBot is a modular robotic planning framework that combines Large Language Models and Knowledge Graphs to generate feasible and risk-aware plans despite ambiguities in natural language instructions and correctly analyzing the objects present in the environment - challenges that typically arise from a lack of commonsense reasoning. To do that, ConceptBot integrates (i) an Object Property Extraction (OPE) module that enriches scene understanding with semantic concepts from ConceptNet, (ii) a User Request Processing (URP) module that disambiguates and structures instructions, and (iii) a Planner that generates context-aware, feasible pick-and-place policies. In comparative evaluations against Google SayCan, ConceptBot achieved 100% success on explicit tasks, maintained 87% accuracy on implicit tasks (versus 31% for SayCan), reached 76% on risk-aware tasks (versus 15%), and outperformed SayCan in application-specific scenarios, including material classification (70% vs. 20%) and toxicity detection (86% vs. 36%). On SafeAgentBench, ConceptBot achieved an overall score of 80% (versus 46% for the next-best baseline). These results, validated in both simulation and laboratory experiments, demonstrate ConceptBot's ability to generalize without domain-specific training and to significantly improve the reliability of robotic policies in unstructured environments. Website: https://sites.google.com/view/conceptbot
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