Search Results for author:
Found 5 papers, 3 papers with code
AGL-NET: Aerial-Ground Cross-Modal Global Localization with Varying Scales
We present AGL-NET, a novel learning-based method for global localization using LiDAR point clouds and satellite maps.
On the Safety Concerns of Deploying LLMs/VLMs in Robotics: Highlighting the Risks and Vulnerabilities
However, such integration can introduce significant vulnerabilities, in terms of their susceptibility to adversarial attacks due to the language models, potentially leading to catastrophic consequences.
HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models
Our comprehensive case studies within HallusionBench shed light on the challenges of hallucination and illusion in LVLMs.
Ranked #1 on
Visual Question Answering (VQA)
on HallusionBench
iPLAN: Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement Learning
Our approach for intent-aware planning, iPLAN, allows agents to infer nearby drivers' intents solely from their local observations.
FireCommander: An Interactive, Probabilistic Multi-agent Environment for Heterogeneous Robot Teams
The FireCommander environment can be useful for research topics spanning a wide range of applications from Reinforcement Learning (RL) and Learning from Demonstration (LfD), to Coordination, Psychology, Human-Robot Interaction (HRI) and Teaming.
