SkateNav: Learning Energy-Efficient Navigation through Adaptive Skating on Passive-Wheel Quadrupedal Robots
To address these challenges, we propose SkateNav, a unified skating-navigation framework based on reinforcement learning.
ProofPaper ↗
Key points
- Passive-wheel quadrupedal robots offer energy-efficient locomotion through leg-driven propulsion and momentum-driven gliding.
- Velocity-tracking objectives may suppress the speed variations inherent in skating, discouraging efficient gliding.
- An adaptive skating cycle structures gliding, pushing, and recovery, while frequency modulation at every control step adjusts phase durations to navigation demands.
- Real-world experiments demonstrate zero-shot transfer from simulation to a passive-wheel Mini Cheetah across cluttered indoor spaces, slopes, and paved outdoor surfaces.
Sources (1)
- [1]SkateNav: Learning Energy-Efficient Navigation through Adaptive Skating on Passive-Wheel Quadrupedal RobotsarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 07:55 AM
To address these challenges, we propose SkateNav, a unified skating-navigation framework based on reinforcement learning.
Passive-wheel quadrupedal robots offer energy-efficient locomotion through leg-driven propulsion and momentum-driven gliding.
Extractive summary: sentences quoted from the sources.
Before this
- Oct 19, 2026HarnessRL: Co-Evolving Policies with a Just-in-Time Training Harness for Open-Ended RL
- Oct 19, 2026TorchNeuron: running HF models on AWS Trainium is easier than ever
- Oct 18, 2026Google Open-Sources Harness2, a Recursive Agent Harnessing Framework
- Oct 18, 2026Elevatormusic/DeepSeek-V4.1-Flash-1017-EXL3-TensorFold-2x-DGX-Spark: DeepSeek-V4.1-Flash-1017 EXL3 2.9bpw on 2x NVIDIA DGX Spark (GB10) with TensorFold: 2.1-2.3x the vLLM kit's decode speed.
- Oct 18, 2026Think Visually Across Space and Time: Grounded Reasoning for Video Segmentation
- Oct 16, 2026Learning Robot Metareasoning: Adaptive Computation Budgets for Real-Time Control