ODYSSEY: Open-World Quadrupeds Exploration and Manipulation for
  Long-Horizon Tasks
Authors: name: Kaijun Wang; name: Liqin Lu; name: Mingyu Liu; name: Jianuo Jiang; name: Zeju Li; name: Bolin Zhang; name: Wancai Zheng; name: Xinyi Yu; name: Hao Chen; name: Chunhua Shen
Published: 2025-08-11 17:54:31

Abstract: Language-guided long-horizon mobile manipulation has long been a grand
challenge in embodied semantic reasoning, generalizable manipulation, and
adaptive locomotion. Three fundamental limitations hinder progress: First,
although large language models have improved spatial reasoning and task
planning through semantic priors, existing implementations remain confined to
tabletop scenarios, failing to address the constrained perception and limited
actuation ranges of mobile platforms. Second, current manipulation strategies
exhibit insufficient generalization when confronted with the diverse object
configurations encountered in open-world environments. Third, while crucial for
practical deployment, the dual requirement of maintaining high platform
maneuverability alongside precise end-effector control in unstructured settings
remains understudied.
  In this work, we present ODYSSEY, a unified mobile manipulation framework for
agile quadruped robots equipped with manipulators, which seamlessly integrates
high-level task planning with low-level whole-body control. To address the
challenge of egocentric perception in language-conditioned tasks, we introduce
a hierarchical planner powered by a vision-language model, enabling
long-horizon instruction decomposition and precise action execution. At the
control level, our novel whole-body policy achieves robust coordination across
challenging terrains. We further present the first benchmark for long-horizon
mobile manipulation, evaluating diverse indoor and outdoor scenarios. Through
successful sim-to-real transfer, we demonstrate the system's generalization and
robustness in real-world deployments, underscoring the practicality of legged
manipulators in unstructured environments. Our work advances the feasibility of
generalized robotic assistants capable of complex, dynamic tasks. Our project
page: https://kaijwang.github.io/odyssey.github.io/