22 citations · 34 across the 23 of their papers we have counts for
7 papers · 1 filter
Learning Continuous Neural Representation of Stochastic Hybrid Systems
Sangli Teng, Hang Liu, Koushil Sreenath
A stochastic hybrid system (SHS) is governed by a stochastic differential equation (SDE) describing the continuous dynamics and a Markov reset kernel triggered on the guard surface…
ODEWorld: A Continuous Predictive Architecture via Physical-Time Flow
Dongxiu Liu, Haoyi Niu, Peng Cheng +5
In the physical world we inhabit, space and time are fundamentally continuous. However, existing machine learning paradigms for world modeling are largely confined to discrete-time…
Embedding Hybrid Systems into Continuous Latent Vector Fields
Sangli Teng, Hang Liu, Koushil Sreenath
This work proves that an -dimensional hybrid system can be embedded into an -dimensional Euclidean space equipped with a continuous vector field on its embedded image wheneve…
LieIPM: Lie Group Interior Point Method for Direct Trajectory Optimization of Rigid Bodies
Sangli Teng, Ruiqi Zhang, Tzu-Yuan Lin +5
Designing dynamically feasible trajectories for rigid bodies is a fundamental problem in robotics. While direct methods are widely used, the existing constrained optimizers typical…
A Survey of Legged Robotics in Non-Inertial Environments: Past, Present, and Future
I-Chia Chang, Xinyan Huang, Tzu-Yuan Lin +5
Legged robots have demonstrated remarkable agility on rigid, stationary ground, but their locomotion reliability remains limited in non-inertial environments, where the supporting…
Stein Variational Ergodic Surface Coverage with SE(3) Constraints
Jiayun Li, Yufeng Jin, Sangli Teng +2
Surface manipulation tasks require robots to generate trajectories that comprehensively cover complex 3D surfaces while maintaining precise end-effector poses. Existing ergodic tra…
MePoly: Max Entropy Polynomial Policy Optimization
Hang Liu, Sangli Teng, Maani Ghaffari
Stochastic Optimal Control provides a unified mathematical framework for solving complex decision-making problems, encompassing paradigms such as maximum entropy reinforcement lear…