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Zhiqiang Sui

7 accepted papers

2025

An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization

ICRA 2025

Multi-sensor fusion is essential for autonomous vehicle localization, as it is capable of integrating data from various sources for enhanced accuracy and reliability. The accuracy of the integrated location and orientation depends on the precision of the uncertainty modeling. Traditional methods of

Cited by 2SourceScholar
2020

GeoFusion: Geometric Consistency Informed Scene Estimation in Dense Clutter

RA-L 2020

We propose GeoFusion, a SLAM-based scene estimation method for building an object-level semantic map in dense clutter. In dense clutter, objects are often in close contact and severe occlusions, which brings more false detections and noisy pose estimates from existing perception methods. To solve th

Cited by 10SourceScholar
2019

GRIP: Generative Robust Inference and Perception for Semantic Robot Manipulation in Adversarial Environments

IROS 2019poster

Recent advancements have led to a proliferation of machine learning systems used to assist humans in a wide range of tasks. However, we are still far from accurate, reliable, and resource-efficient operations of these systems. For robot perception, convolutional neural networks (CNNs) for object det…

Cited by 38SourceScholar
2018

Plenoptic Monte Carlo Object Localization for Robot Grasping Under Layered Translucency

IROS 2018poster

In order to fully function in human environments, robot perception needs to account for the uncertainty caused by translucent materials. Translucency poses several open challenges in the form of transparent objects (e.g., drinking glasses), refractive media (e.g., water), and diffuse partial occlusi…

Cited by 15SourceScholar
2018

Semantic Robot Programming for Goal-Directed Manipulation in Cluttered Scenes

ICRA 2018poster

We present the Semantic Robot Programming (SRP) paradigm as a convergence of robot programming by demonstration and semantic mapping. In SRP, a user can directly program a robot manipulator by demonstrating a snapshot of their intended goal scene in workspace. The robot then parses this goal as a sc…

Cited by 55SourceScholar
2015

Axiomatic particle filtering for goal-directed robotic manipulation

IROS 2015poster

Manipulation tasks involving sequential pick-and-place actions in human environments remains an open problem for robotics. Central to this problem is the inability for robots to perceive in cluttered environments, where objects are physically touching, stacked, or occluded from the view. Such physic…

Cited by 36SourceScholar