activity
20222026
most citedAffordance-Driven Next-Best-View Planning for Robotic Grasping

6 citations · 8 across the 11 of their papers we have counts for

collaborators

12 papers

cs.RO2026

FinsSim: A Reality-Aligned Integrated Simulation Platform for Underwater Robot Learning

Yu Zhang, Yuanmingqing Song, Xiangyun Rao +4

Underwater robot learning relies on simulators that integrate high-fidelity hydrodynamics, convenient learning interfaces, and a credible transition to real scenarios. In this work…

cs.RO2026

Underwater Visual Target Tracking with Target-Specific Depth Estimation and Adaptive Model-Fusion Predictive Control

Yuheng Zhou, Haiyang Cheng, Yanqi Feng +5

Vision-based underwater target tracking is challenged by unreliable depth measurements and unknown target motion. This paper proposes a stereo visual-servoing framework for an auto…

cs.RO2025

Aucamp: An Underwater Camera-Based Multi-Robot Platform with Low-Cost, Distributed, and Robust Localization

Jisheng Xu, Ding Lin, Pangkit Fong +3

This paper introduces an underwater multi-robot platform, named Aucamp, characterized by cost-effective monocular-camera-based sensing, distributed protocol and robust orientation…

eess.SY2024

Smart Predict-then-Optimize Method with Dependent Data: Risk Bounds and Calibration of Autoregression

Jixian Liu, Tao Xu, Jianping He +1

The predict-then-optimize (PTO) framework is indispensable for addressing practical stochastic decision-making tasks. It consists of two crucial steps: initially predicting unknown…

math.OC2023

Heuristic Learning for Co-Design Scheme of Optimal Sequential Attack

Xiaoyu Luo, Haoxuan Pan, Chongrong Fang +3

This paper considers a novel co-design problem of the optimal \textit{sequential} attack, whose attack strategy changes with the time series, and in which the \textit{sequential} a…

cs.RO2023★ 6 cited

Affordance-Driven Next-Best-View Planning for Robotic Grasping

Xuechao Zhang, Dong Wang, Sun Han +7

Grasping occluded objects in cluttered environments is an essential component in complex robotic manipulation tasks. In this paper, we introduce an AffordanCE-driven Next-Best-View…