机器人任务规划中场景图充分性的信息空间视角
An Information-Space Perspective to Scene Graph Sufficiency for Robotic Task Planning
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- Maastricht University（马斯特里赫特大学）
- Aalto University（阿尔托大学）
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中文总结 AI 辅助
本文提出信息空间框架下的场景图充分性形式化，通过信息映射和商转换系统定义充分条件，确保派生计划在最大系统上可行。
中文摘要 AI 辅助
复杂环境中的规划需要任务规范，这些规范基于能够捕捉对象、关系和可供性的表示；场景图满足了这一需求，但其在大规模环境中的规模阻碍了高效规划。虽然已经探索了任务感知剪枝和层次抽象，但对于什么构成规划所需的充分场景图，仍缺乏一种通用的、以任务为中心的正式化。本文通过定义场景图转换系统和导航与操作的相关动作语义，在信息空间框架内对场景图上的规划进行建模，从而提供了这样的正式化。然后，我们通过信息映射引入派生场景图，这些映射合并和剪枝节点，并诱导出用运动原语增强的商转换系统，以捕捉合并图节点上的高层动作。充分性由两个条件表征：（i）信息映射产生确定性商，（ii）任务在派生轨迹上是适定的，确保在派生模型上找到的计划在最大系统上是可行的。我们使用一个示例环境中的任务来说明该框架，展示了充分和不足的简化场景图。
英文摘要
Planning in complex environments requires task specifications grounded in representations that capture objects, relations, and affordances; scene graphs meet this need, but their size in large environments hinders efficient planning. While task-aware pruning and hierarchical abstractions have been explored, a general, task-centric formalization of what constitutes a sufficient scene graph for planning remains open. This paper provides such a formalization by modeling planning over scene graphs within an information-spaces framework through the definition of scene graph transition systems and relevant action semantics for navigation and manipulation. We then introduce derived scene graphs via information mappings that merge and prune nodes and induce quotient transition systems augmented with motion primitives to capture higher-level actions over merged graph nodes. Sufficiency is characterized by two conditions: (i) the information mapping yields a deterministic quotient, and (ii) the task is well-posed over derived traces, ensuring plans found on the derived model are feasible on the maximal system. We illustrate the framework using a task over an example environment, showing both sufficient and insufficient reduced scene graphs.
