9 papers
Safe Streaming Flow Planning by Aligning Sampling Dynamics with Execution Dynamics
Seunghwan Jang, Jeongyong Yang, Siddharth Ancha +1
Generative planners based on diffusion/flow matching can learn to synthesize long-horizon trajectories from demonstrations. However, real-world deployment requires (i) enforcing sa…
SymVD: Symmetric Vision Language Action Distillation for Robot Manipulation
Hyewon Choi, Donggyu Kim, Soojean Han
While pretrained Vision-Language-Action (VLA) models offer broad generalization capabilities in robotic manipulation tasks, adapting them to real-world environments or handling tas…
Graph-Guided Safe Diffuser: Topological Graph Guidance for Safe Diffusion Planning
Nakgyu Yang, KwangBin Lee, SooJean Han
Many diffusion-based planners enforce safety through inference-time guidance, but such interleaved trajectory deformations often degrade kinematic feasibility due to manifold ruptu…
Systematic Hazard Sampling: Minimal-Variance Inference for Discrete Diffusion and Flow Models
Seunghwan Jang, SooJean Han, Wonje Jeung
Uniform-noise discrete diffusion and flow models generate sequences non-autoregressively through iterative, context-dependent token replacements. However, these models are typicall…
CFG-OEC: Classifier Free Guidance with Orthogonal Error Correction
Nakgyu Yang, Yechan Lee, SooJean Han
Classifier free guidance is a standard method for conditional sampling in diffusion models, but its sampling rule is not aligned with the objective used in training. This mismatch…
SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functions
Jeongyong Yang, Seunghwan Jang, SooJean Han
Generative planners based on flow matching (FM) produce high-quality paths in a single or a few ODE steps, but their sampling dynamics offer no formal safety guarantees and can yie…
Advantages of Feedback in Distributed Data-Gathering for Accurate and Power-Efficient State-Estimation
Hyeongmin Choe, SooJean Han
In distributed target-tracking sensor networks, efficient data gathering methods are necessary to save communication resources and assure information accuracy. This paper proposes…
Heterogeneous Predictor-based Risk-Aware Planning with Conformal Prediction in Dense, Uncertain Environments
Jeongyong Yang, KwangBin Lee, SooJean Han
Real-time planning among many uncertain, dynamic obstacles is challenging because predicting every agent with high fidelity is both unnecessary and computationally expensive. We pr…
Efficient Replay Memory Architectures in Multi-Agent Reinforcement Learning for Traffic Congestion Control
Mukul Chodhary, Kevin Octavian, SooJean Han
Episodic control, inspired by the role of episodic memory in the human brain, has been shown to improve the sample inefficiency of model-free reinforcement learning by reusing high…