59 citations · 183 across the 41 of their papers we have counts for
42 papers
Wiring Matters: Injection Topology and Initialization of Affordance Heads in Vision-Language-Action Policies
Zijian An, Linhan Wang, Jiayan Wang +4
Dense affordance supervision is an appealing auxiliary signal for vision-language-action (VLA) policies, yet naively co-training an affordance head can severely damage instruction…
Project SCOUT: Interceptor Drone for Perimeter Defense
Azmain Yousuf, Siwei Cai, Knut Peterson +2
The rapid proliferation of unauthorized unmanned aerial vehicles (UAVs) has created a growing need for robust, jamming-resistant counter-UAV systems for perimeter defense. This pap…
GlanceWAM: Sparse Test-Time Imagination for World-Action Models
Linhan Wang, Zijian An, Mingyuan Zhang +8
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 contr…
Latent World Models with Monotone Planning Costs for Image-Goal Navigation
Amirhosein Chahe, Siwei Cai, Lifeng Zhou
Image-goal navigation with latent world models requires not only accurate future prediction, but also a planning cost that reliably ranks candidate action sequences. We define the…
TransGraspNet: Physically and Geometrically Consistent Manipulation of Transparent Labware
Hailing Hu, Mingyi Zhu, Yiquan An +3
Manipulating transparent laboratory glassware that contains liquid is inherently safety-critical: even small geometric errors can cause unstable grasps and hazardous spillage. Alth…
What's Hidden Matters: Identifying Planning-Critical Occluded Agents using Vision-Language Models
Amirhosein Chahe, Tyler Naes, Jovin D'sa +4
Autonomous vehicles must safely navigate complex environments where planning-critical agents may be hidden from view. Current approaches often treat all occlusions with uniform con…
Threading Optimization for Vision-Language-Action Model Inference in Low-Cost Smart Agricultural Manipulation
Keith Truongcao, Christopher Nhu, Zijian An +3
Vision-Language Action (VLA) models continue to face challenges such as slow inference speed and difficulty performing fine-grained motion adjustments, limiting their widespread ad…
ROG-Grasp: Root-Oriented Geometry for Robotic Grasping and Placement
Zijian An, Augustus Sroka, Ran Yang +8
Orientation-aware manipulation is essential in post-harvest agricultural processing, where produce must be grasped and placed in consistent configurations. This paper presents ROG-…
VILAS: A VLA-Integrated Low-cost Architecture with Soft Grasping for Robotic Manipulation
Zijian An, Hadi Khezam, Bill Cai +5
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 h…
AGT-CV: An Aerial-Ground Team Cross-View Dataset for Heterogeneous Robot Teams in Unstructured Environments
Siwei Cai, Knut Peterson, Quan Tran +7
Heterogeneous air-ground robot teams combine complementary sensing modalities, mobility characteristics, and spatial viewpoints that can significantly enhance perception in complex…
Vision Language Models Cannot Plan, but Can They Formalize?
Muyu He, Yuxi Zheng, Yuchen Liu +7
The advancement of vision language models (VLMs) has empowered embodied agents to accomplish simple multimodal planning tasks, but not long-horizon ones requiring long sequences of…
CLAW: A Vision-Language-Action Framework for Weight-Aware Robotic Grasping
Zijian An, Ran Yang, Yiming Feng +1
Vision-language-action (VLA) models have recently emerged as a promising paradigm for robotic control, enabling end-to-end policies that ground natural language instructions into v…
Query3D: LLM-Powered Open-Vocabulary Scene Segmentation with Language Embedded 3D Gaussian
Amirhosein Chahe, Lifeng Zhou
This paper introduces a novel method for open-vocabulary 3D scene querying in autonomous driving by combining Language Embedded 3D Gaussians with Large Language Models (LLMs). We p…
Multi-Robot Target Tracking with Sensing and Communication Danger Zones
Jiazhen Liu, Peihan Li, Yuwei Wu +3
Multi-robot target tracking finds extensive applications in different scenarios, such as environmental surveillance and wildfire management, which require the robustness of the pra…
Challenges Faced by Large Language Models in Solving Multi-Agent Flocking
Peihan Li, Vishnu Menon, Bhavanaraj Gudiguntla +2
Flocking is a behavior where multiple agents in a system attempt to stay close to each other while avoiding collision and maintaining a desired formation. This is observed in the n…
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 defen…
Monte-Carlo Tree Search for Behavior Planning in Autonomous Driving
Qianfeng Wen, Zhongyi Gong, Lifeng Zhou +1
The integration of autonomous vehicles into urban and highway environments necessitates the development of robust and adaptable behavior planning systems. This study presents an in…
Learning Decentralized Flocking Controllers with Spatio-Temporal Graph Neural Network
Siji Chen, Yanshen Sun, Peihan Li +2
Recently a line of researches has delved the use of graph neural networks (GNNs) for decentralized control in swarm robotics. However, it has been observed that relying solely on t…
Energy-Aware Routing Algorithm for Mobile Ground-to-Air Charging
Bill Cai, Fei Lu, Lifeng Zhou
We investigate the problem of energy-constrained planning for a cooperative system of an Unmanned Ground Vehicles (UGV) and an Unmanned Aerial Vehicle (UAV). In scenarios where the…
Context-Aware Entity Grounding with Open-Vocabulary 3D Scene Graphs
Haonan Chang, Kowndinya Boyalakuntla, Shiyang Lu +8
We present an Open-Vocabulary 3D Scene Graph (OVSG), a formal framework for grounding a variety of entities, such as object instances, agents, and regions, with free-form text-base…
Assignment Algorithms for Multi-Robot Multi-Target Tracking with Sufficient and Limited Sensing Capability
Peihan Li, Lifeng Zhou
We study the problem of assigning robots with actions to track targets. The objective is to optimize the robot team's tracking quality which can be defined as the reduction in the…
Graph Neural Networks for Decentralized Multi-Agent Perimeter Defense
Elijah S. Lee, Lifeng Zhou, Alejandro Ribeiro +1
In this work, we study the problem of decentralized multi-agent perimeter defense that asks for computing actions for defenders with local perceptions and communications to maximiz…
D2CoPlan: A Differentiable Decentralized Planner for Multi-Robot Coverage
Vishnu Dutt Sharma, Lifeng Zhou, Pratap Tokekar
Centralized approaches for multi-robot coverage planning problems suffer from the lack of scalability. Learning-based distributed algorithms provide a scalable avenue in addition t…
Active Metric-Semantic Mapping by Multiple Aerial Robots
Xu Liu, Ankit Prabhu, Fernando Cladera +4
Traditional approaches for active mapping focus on building geometric maps. For most real-world applications, however, actionable information is related to semantically meaningful…