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cs.RO2024
Imagine-2-Drive: Leveraging High-Fidelity World Models via Multi-Modal Diffusion Policies
Anant Garg, K Madhava Krishna
World Model-based Reinforcement Learning (WMRL) enables sample efficient policy learning by reducing the need for online interactions which can potentially be costly and unsafe, es…
cs.RO2024
Towards Global Localization using Multi-Modal Object-Instance Re-Identification
Aneesh Chavan, Vaibhav Agrawal, Vineeth Bhat +4
Re-identification (ReID) is a critical challenge in computer vision, predominantly studied in the context of pedestrians and vehicles. However, robust object-instance ReID, which h…
cs.RO2024
LeGo-Drive: Language-enhanced Goal-oriented Closed-Loop End-to-End Autonomous Driving
Pranjal Paul, Anant Garg, Tushar Choudhary +2
Existing Vision-Language models (VLMs) estimate either long-term trajectory waypoints or a set of control actions as a reactive solution for closed-loop planning based on their ric…