activity
20242026
most citedSeePerSea: Multi-modal Perception Dataset of In-water Objects for Autonomous Surface Vehicles

8 citations · 8 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Manipulider: A Multi-Engine Buoyancy-Controlled Robot for Thrusterless Underwater Gliding and Manipulation

Yitao Jiang, Yewei Huang, Weizhi Cao +5

The Manipulider is a buoyancy-actuated underwater robot that enables thrusterless, glide-like locomotion and attitude-based manipulation, while providing a magnetic modular interfa…

cs.RO2026

RENEW: Risk- and Energy-Aware Navigation in Dynamic Waterways

Mingi Jeong, Alberto Quattrini Li

We present RENEW, a global path planner for Autonomous Surface Vehicle (ASV) in dynamic environments with external disturbances (e.g., water currents). RENEW introduces a unified r…

cs.RO2025

Multi-Object Active Search and Tracking by Multiple Agents in Untrusted, Dynamically Changing Environments

Mingi Jeong, Cristian Molinaro, Tonmoay Deb +5

This paper addresses the problem of both actively searching and tracking multiple unknown dynamic objects in a known environment with multiple cooperative autonomous agents with pa…

cs.RO2024

Active Learning-augmented Intention-aware Obstacle Avoidance of Autonomous Surface Vehicles in High-traffic Waters

Mingi Jeong, Arihant Chadda, Alberto Quattrini Li

This paper enhances the obstacle avoidance of Autonomous Surface Vehicles (ASVs) for safe navigation in high-traffic waters with an active state estimation of obstacle's passing in…

cs.RO2024

An Untethered Bioinspired Robotic Tensegrity Dolphin with Multi-Flexibility Design for Aquatic Locomotion

Luyang Zhao, Yitao Jiang, Chun-Yi She +5

This paper presents the first steps toward a soft dolphin robot using a bio-inspired approach to mimic dolphin flexibility. The current dolphin robot uses a minimalist approach, wi…

cs.RO2024

Robust Perception and Navigation of Autonomous Surface Vehicles in Challenging Environments

Mingi Jeong

Research on coastal regions traditionally involves methods like manual sampling, monitoring buoys, and remote sensing, but these methods face challenges in spatially and temporally…

cs.RO2024★ 8 cited

SeePerSea: Multi-modal Perception Dataset of In-water Objects for Autonomous Surface Vehicles

Mingi Jeong, Arihant Chadda, Ziang Ren +8

This paper introduces the first publicly accessible labeled multi-modal perception dataset for autonomous maritime navigation, focusing on in-water obstacles within the aquatic env…