An Information-Space Perspective to Scene Graph Sufficiency for Robotic Task Planning

2026-09-14

AI Summary

本文通过信息空间框架定义场景图转换系统及动作语义，提出了一种任务导向的场景图充分性形式化方法，解决了复杂环境中机器人任务规划效率问题。

Abstract

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.

Problem

• scene graph
• task planning
• information space
• sufficiency
• complex environments

Innovation

• information-space
• scene graph sufficiency
• task planning
• transition systems
• information mappings