Zijian An

Process-aware robotic food assembly: Closed-loop visual monitoring across heterogeneous ingredients

Ran Yang, Zijian An, Lifeng Zhou, Yiming Feng

In this study, process cognition refers to the ability to monitor the state of the current food-placement subtask and autonomously advance through a predefined assembly sequence without manual intervention during execution. Current robotic systems address isolated operations but cannot navigate sequential procedures …

us (code pays fourni par la source)

GlanceWAM: Sparse Test-Time Imagination for World-Action Models

Linhan Wang, Zijian An, Mingyuan Zhang, Chen Dai et autres

Video generative models provide rich physical priors for robot learning, yet existing world-action models (WAMs) face a fundamental trade-off: synchronous video generation at control rate is latency-prohibitive, while abandoning test-time visual imagination sacrifices task success. We show that visual imagination achieves both …

Large language models for multi-robot systems: a survey

Peihan Li, Zijian An, Lifeng Zhou

Abstract The rapid advancement of Large Language Models (LLMs) has opened new possibilities in Multi-Robot Systems (MRS), enabling enhanced communication, task allocation and planning, and human-robot interaction. Unlike traditional single-robot and multi-agent systems, MRS poses unique challenges, including coordination, scalability, and real-world …

us (code pays fourni par la source)

Threading Optimization for Vision-Language-Action Model Inference in Low-Cost Smart Agricultural Manipulation

Keith Truongcao, Christopher Nhu, Zijian An, Phong Van Nguyen et autres

Vision-Language Action (VLA) models continue to face challenges such as slow inference speed and difficulty performing fine-grained motion adjustments, limiting their widespread adoption in industry. While the Real-Time Action Chunking (RTAC) algorithm has been proposed to address these bottlenecks, bridging the gap …

ROG-Grasp: Root-Oriented Geometry for Robotic Grasping and Placement

Zijian An, Augustus Sroka, Ran Yang, Bill Cai et autres

Orientation-aware manipulation is essential in post-harvest agricultural processing, where produce must be grasped and placed in consistent configurations. This paper presents ROG-Grasp, a geometry-based robotic grasping and placement framework that estimates the produce orientation from root surface geometry using RGB-D perception. A …

VILAS: A VLA-Integrated Low-cost Architecture with Soft Grasping for Robotic Manipulation

Zijian An, Hadi Khezam, Bill Cai, Ran Yang et autres

We present VILAS, a fully low-cost, modular robotic manipulation platform designed to support end-to-end vision-language-action (VLA) policy learning and deployment on accessible hardware. The system integrates a Fairino FR5 collaborative arm, a Jodell RG52-50 electric gripper, and a dual-camera perception module, unified …

Reinforcement Learning for Game-Theoretic Resource Allocation on Graphs

Zijian An, Lifeng Zhou

Game-theoretic resource allocation on graphs (GRAG) involves two players competing over multiple steps to control nodes of interest on a graph, a problem modeled as a multi-step Colonel Blotto Game (MCBG). Finding optimal strategies is challenging due to the dynamic action space …

us (code pays fourni par la source)

SeqVLA: Sequential Task Execution for Long-Horizon Manipulation with Completion-Aware Vision-Language-Action Model

Yang Ran, Zijian An, Yiming Feng

Long-horizon robotic manipulation tasks require executing multiple interdependent subtasks in strict sequence, where errors in detecting subtask completion can cascade into downstream failures. Existing Vision-Language-Action (VLA) models such as $π_0$ excel at continuous low-level control but lack an internal signal for identifying …

Reinforcement Learning for Game-Theoretic Resource Allocation on Graphs

Zijian An, Lifeng Zhou

Game-theoretic resource allocation on graphs (GRAG) involves two players competing over multiple steps to control nodes of interest on a graph, a problem modeled as a multi-step Colonel Blotto Game (MCBG). Finding optimal strategies is challenging due to the dynamic action space …

Double Oracle Algorithm for Game-Theoretic Robot Allocation on Graphs

Zijian An, Lifeng Zhou

We study the problem of game-theoretic robot allocation where two players strategically allocate robots to compete for multiple sites of interest. Robots possess offensive or defensive capabilities to interfere and weaken their opponents to take over a competing site. This problem belongs …

us (code pays fourni par la source)

A Study of Crop Yield Prediction Based on Backpropagation Artificial Neural Network (BP- ANN)

Zijian An, Jianghong Zheng, Zheng Zhang, Di Wu et autres

Under the background of food security, the research of crop growth models has attracted much attention. There is an urgent need for simplified crop yield forecasting methods based on environmental factors while maintaining as much accuracy as possible. Firstly, 18 years of …

cn (code pays fourni par la source)

High-order statistically derived combinations of geometric features for handprinted character recognition

Atul K. K. Chhabra, Zijian An, D. Balick, G. Cerf et autres

An intelligent character recognition (ICR) system for offline recognition of isolated handprinted characters is presented. The system comprises a feature extraction stage and a classifier (a feedforward network) that is trained using error backpropagation. The feature extraction stage consists of two steps. …

us (code pays fourni par la source)