5 papers · 1 filter
Learning Communication-Conditioned Generative Policies for Decentralized Multi-Agent Collision Avoidance
Prajwal Koirala, Mark Campbell
In this work, we propose a decentralized communication-conditioned generative framework for multi-agent collision avoidance. Agents generate short-horizon action sequences using a…
VGFM: Expressive Robot Policies via Dense Value Guidance in Flow Matching
Prajwal Koirala, Mark Campbell
Recent robot learning paradigms increasingly rely on large offline datasets of robotic interactions to train control policies. Expressive generative models enable rich and multimod…
LCLA: Language-Conditioned Latent Alignment for Vision-Language Navigation
Nitesh Subedi, Adam Haroon, Samuel Tetteh +3
We propose LCLA (Language-Conditioned Latent Alignment), a framework for vision-language navigation that learns modular perception-action interfaces by aligning sensory observation…
Can Pretrained Vision-Language Embeddings Alone Guide Robot Navigation?
Nitesh Subedi, Adam Haroon, Shreyan Ganguly +4
Foundation models have revolutionized robotics by providing rich semantic representations without task-specific training. While many approaches integrate pretrained vision-language…
F1tenth Autonomous Racing With Offline Reinforcement Learning Methods
Prajwal Koirala, Cody Fleming
Autonomous racing serves as a critical platform for evaluating automated driving systems and enhancing vehicle mobility intelligence. This work investigates offline reinforcement l…