15 citations · 26 across the 5 of their papers we have counts for
5 papers
DS-K3DOM: 3-D Dynamic Occupancy Mapping with Kernel Inference and Dempster-Shafer Evidential Theory
Juyeop Han, Youngjae Min, Hyeok-Joo Chae +2
Occupancy mapping has been widely utilized to represent the surroundings for autonomous robots to perform tasks such as navigation and manipulation. While occupancy mapping in 2-D…
Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning
Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae +2
We present a hierarchical planning and control framework that enables an agent to perform various tasks and adapt to a new task flexibly. Rather than learning an individual policy…
Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems
Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae +2
We present a representation learning algorithm that learns a low-dimensional latent dynamical system from high-dimensional \textit{sequential} raw data, e.g., video. The framework…
Approximate Inference-based Motion Planning by Learning and Exploiting Low-Dimensional Latent Variable Models
Jung-Su Ha, Hyeok-Joo Chae, Han-Lim Choi
This work presents an efficient framework to generate a motion plan of a robot with high degrees of freedom (e.g., a humanoid robot). High-dimensionality of the robot configuration…
Optimal Control-Based UAV Path Planning with Dynamically-Constrained TSP with Neighborhoods
Dae-Sung Jang, Hyeok-Joo Chae, Han-Lim Choi
This paper addresses path planning of an unmanned aerial vehicle (UAV) with remote sensing capabilities (or wireless communication capabilities). The goal of the path planning is t…