# REST: Receding Horizon Explorative Steiner Tree for Zero-Shot Object-Goal Navigation

Paper: [arXiv:2603.18624](https://arxiv.org/abs/2603.18624)

## Core Idea

This paper tackles exploration in unknown environments by planning toward informative frontiers, revising the plan as new observations arrive, and using a tree-structured search strategy to reach likely goals efficiently.

## Why It Matters Here

This repo does not do embodied navigation, but it does have a similar search problem when a user is trying to inspect a long, branching trace.

The transfer is about exploration strategy:

- do not inspect everything
- choose promising frontiers
- update the route as new evidence appears

## Key Takeaways For The Repo

### 1. Large trace spaces need guided exploration

When a session branches heavily, users need help deciding which branch or checkpoint to inspect next. A useful debugger can prioritize:

- branches near failures
- branches with unusual novelty or severity
- branches with weak evidence or missing checkpoints

### 2. Navigation should be horizon-based, not fully committed

The system does not need to solve the whole trace graph at once. It can recommend the next useful move, then revise after each inspection.

### 3. Tree structure can drive branch search

The current decision tree can become more useful if it helps users move toward the most informative unexplored path instead of only rendering the whole structure.

## Concrete Opportunities

- score trace frontiers for relevance, novelty, and failure proximity
- add "next most informative branch" actions to the decision tree
- guide replay toward checkpoints and branches that reduce uncertainty fastest
- surface exploration paths for long sessions with many branches

## Caution

This paper is the weakest direct match to the repo because it is about navigation, not debugging. The correct transfer is the search strategy, not the robotics-specific formulation.

## Best Next Experiment

Add one exploration aid to the decision tree:

- identify uninspected branches near a failure
- rank the top candidates
- let the user jump directly to the most informative next branch
