Embodied Tree of Thoughts: Deliberate Manipulation Planning with Embodied World Model

TL;DR

The paper introduces Embodied Tree of Thoughts (EToT), a physics-grounded planning framework for robot manipulation that combines semantic reasoning and failure diagnosis to improve long-horizon task success.

Contribution

EToT is a novel framework that integrates a physics-based digital twin with tree search, enabling more accurate and physically consistent manipulation planning.

Findings

EToT outperforms baselines on manipulation tasks.

Effective failure diagnosis and correction improve planning robustness.

Physics grounding ensures adherence to physical constraints.

Abstract

World models have emerged as a pivotal component in robot manipulation planning, enabling agents to predict future environmental states and reason about the consequences of actions before execution. While video-generation models are increasingly adopted, they often lack rigorous physical grounding, leading to hallucinations and a failure to maintain consistency in long-horizon physical constraints. To address these limitations, we propose Embodied Tree of Thoughts (EToT), a novel Real2Sim2Real planning framework that leverages a physics-based interactive digital twin as an embodied world model. EToT formulates manipulation planning as a tree search expanded through two synergistic mechanisms: (1) Priori Branching, which generates diverse candidate execution paths based on semantic and spatial analysis; and (2) Reflective Branching, which utilizes VLMs to diagnose execution failures within the simulator and iteratively refine the planning tree with corrective actions. By grounding high-level reasoning in a physics simulator, our framework ensures that generated plans adhere to rigid-body dynamics and collision constraints. We validate EToT on a suite of short- and long-horizon manipulation tasks, where it consistently outperforms baselines by effectively predicting physical dynamics and adapting to potential failures. Website at https://embodied-tree-of-thoughts.github.io .