CycleRL trains a PPO policy in Isaac Sim with domain randomization to achieve 99.9% balance success and direct hardware transfer for autonomous bicycle control.
Dynamic vehicle drifting with nonlinear mpc and a fused kinematic-dynamic bicycle model,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
CycleRL: Sim-to-Real Deep Reinforcement Learning for Robust Autonomous Bicycle Control
CycleRL trains a PPO policy in Isaac Sim with domain randomization to achieve 99.9% balance success and direct hardware transfer for autonomous bicycle control.