An n-dimensional hybrid system embeds into a continuous vector field in m > 2n dimensions, enabling latent Neural ODEs with consistency losses to recover hybrid flows from time series.
Discrete-time hybrid automata learning: Legged locomotion meets skateboarding
5 Pith papers cite this work. Polarity classification is still indexing.
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LieIPM applies a structure-preserving interior point optimizer to rigid-body trajectory planning on Lie groups using variational integrators and closed-form intrinsic derivatives.
PAPL uses phase-conditioned FiLM layers in RL networks to create a unified policy for quadruped robots to ride skateboards by capturing phase-dependent behaviors while sharing knowledge across phases.
HUSKY combines humanoid-skateboard dynamics modeling with adversarial motion priors and physics-guided lean-to-steer strategies to achieve real-world stable skateboarding on a humanoid robot.
A literature survey summarizing modeling, state estimation, control methods, applications, and open challenges for legged robots operating in non-inertial environments where the ground moves or accelerates.
citing papers explorer
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Embedding Hybrid Systems into Continuous Latent Vector Fields
An n-dimensional hybrid system embeds into a continuous vector field in m > 2n dimensions, enabling latent Neural ODEs with consistency losses to recover hybrid flows from time series.
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LieIPM: Lie Group Interior Point Method for Direct Trajectory Optimization of Rigid Bodies
LieIPM applies a structure-preserving interior point optimizer to rigid-body trajectory planning on Lie groups using variational integrators and closed-form intrinsic derivatives.
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Phase-Aware Policy Learning for Skateboard Riding of Quadruped Robots via Feature-wise Linear Modulation
PAPL uses phase-conditioned FiLM layers in RL networks to create a unified policy for quadruped robots to ride skateboards by capturing phase-dependent behaviors while sharing knowledge across phases.
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HUSKY: Humanoid Skateboarding System via Physics-Aware Whole-Body Control
HUSKY combines humanoid-skateboard dynamics modeling with adversarial motion priors and physics-guided lean-to-steer strategies to achieve real-world stable skateboarding on a humanoid robot.
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A Survey of Legged Robotics in Non-Inertial Environments: Past, Present, and Future
A literature survey summarizing modeling, state estimation, control methods, applications, and open challenges for legged robots operating in non-inertial environments where the ground moves or accelerates.