activity
20162026
most citedFully Distributed Informative Planning for Environmental Learning with Multi-Robot Systems

7 citations · 12 across the 13 of their papers we have counts for

collaborators

15 papers

cs.RO2026

Demonstration of Space Robot Teleoperation over a Lossy and Delayed Network using ATMOS

Inkyu Jang, Gregorio Marchesini, Nicola De Carli +15

We present a demonstration showcasing the Autonomy Testbed for Multi-purpose Orbiting Systems (ATMOS), a planar spacecraft-analog robot designed for hardware-in-the-loop evaluation…

cs.CV2023

Object-based SLAM utilizing unambiguous pose parameters considering general symmetry types

Taekbeom Lee, Youngseok Jang, H. Jin Kim

Existence of symmetric objects, whose observation at different viewpoints can be identical, can deteriorate the performance of simultaneous localization and mapping(SLAM). This wor…

cs.RO2023

Stable Contact Guaranteeing Motion/Force Control for an Aerial Manipulator on an Arbitrarily Tilted Surface

Jeonghyun Byun, Byeongjun Kim, Changhyeon Kim +2

This study aims to design a motion/force controller for an aerial manipulator which guarantees the tracking of time-varying motion/force trajectories as well as the stability durin…

cs.RO2021★ 7 cited

Fully Distributed Informative Planning for Environmental Learning with Multi-Robot Systems

Dohyun Jang, Jaehyun Yoo, Clark Youngdong Son +1

This paper proposes a cooperative environmental learning algorithm working in a fully distributed manner. A multi-robot system is more effective for exploration tasks than a single…

cs.RO2021

Aerial Chasing of a Dynamic Target in Complex Environments

Boseong Felipe Jeon, Changhyeon Kim, Hojoon Shin +1

Rapidly generating an optimal chasing motion of a drone to follow a dynamic target among obstacles is challenging due to numerical issues rising from multiple conflicting objective…

cs.RO2021

Online Distributed Trajectory Planning for Quadrotor Swarm with Feasibility Guarantee using Linear Safe Corridor

Jungwon Park, Dabin Kim, Gyeong Chan Kim +2

This paper presents a new online multi-agent trajectory planning algorithm that guarantees to generate safe, dynamically feasible trajectories in a cluttered environment. The propo…