Agile perceptive multi-skill locomotion for quadrupedal robots in the wild

• URL: http://arxiv.org/abs/2607.13579v1
• Date: Wed, 15 Jul 2026 08:22:52 GMT
• Title: Agile perceptive multi-skill locomotion for quadrupedal robots in the wild
• Abstract summary: APT-RL (Action Pretrained Transformer-based Reinforcement Learning) is a unified framework that enables multi-skill locomotion.<n>Our approach generates large-scale, feature-rich 2D motion datasets through trajectory optimization with simplified dynamics.<n>The resulting high-quality skills serve as strong priors for efficient learning of complex downstream tasks and extend naturally to 3D environments.
• Score: 4.14240816913171
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Enabling quadrupedal robots to traverse complex terrains-from rugged outdoor environments to urban landscapes-requires seamless integration of multiple motor skills, smooth transitions between gaits, and high-speed perceptive locomotion using only onboard sensors. We present APT-RL (Action Pretrained Transformer-based Reinforcement Learning), a unified framework that enables multi-skill locomotion to achieve high-speed traversal in complex environments through autonomous skill transitions utilizing only onboard perception and computation. Our approach generates large-scale, feature-rich 2D motion datasets through trajectory optimization with simplified dynamics. These datasets enable training of diverse, reusable locomotion skills that transfer effectively to a real quadruped robot operating on complex uneven terrains. The resulting high-quality skills serve as strong priors for efficient learning of complex downstream tasks and extend naturally to 3D environments, enabling smooth, high-speed multi-skill locomotion in deployed policy. Real-world experiments demonstrate the framework's capabilities: the robot performs agile maneuvers through complex indoor obstacles and outdoor wild environments, including dynamic drop-down maneuvers that reach instantaneous peak speeds of up to 6 meters per second. A single onboard policy enables robust traversal of diverse obstacles, including stairs, hurdles, stepping stones, gaps, and fallen branches, demonstrating the versatility and effectiveness of our approach.

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