Research blog

XPENG Robotics Multimodal Team builds robots that understand and act in the physical world.

Latest writing

Capek 0.5: An Execution-Centric Vision-Language Model for Embodied Intelligence

An execution-centric vision-language model organized around spatial reasoning, temporal understanding, action guidance, and state verification.

Report

Si0: The Capabilities That Transfer, Perceived Through the Robot's Eyes

The capabilities, data, and sensor alignment behind Si0 as a spatial-intelligence backbone for humanoids.

Report

ROVE: Unlocking Human Interventions for Humanoid Manipulation via Reinforcement Learning

The first human-in-the-loop VLA-RL framework for humanoid robots with dexterous hands.

Paper

AGRA: Making Foresight Actionable in World Action Models

An action-grounded representation alignment objective that bridges visual prediction and robot control in World Action Models.

Paper

Inside Fe0: What Cross-Embodiment Data Teaches an Embodied Foundation Model

A close look at how heterogeneous robot and human data helps an embodied foundation model generalize across visual, semantic, relational, planning, and control axes.

Report

UniT: Toward a Unified Physical Language for Human-to-Humanoid Policy Learning and World Modeling

A unified physical language that maps heterogeneous human and robot motion into shared action primitives.

Paper

DIAL: Decoupling Intent and Action via Latent World Modeling for End-to-End VLA

Latent world modeling that decouples high-level intent from low-level actions in end-to-end vision-language-action policies.

Paper