6 papers
Top-down Traffic Scenario Generation via Joint Initial-Goal Diffusion and Trajectory Infilling
Da Saem Lee, Yash Vardhan Pant, Sebastian Fischmeister
Robust traffic simulators are crucial for developing and testing autonomous vehicles to reduce the costly, labor-intensive real-world data collection process and the need for physi…
Efficient Multi-Objective Planning with Weighted Maximization Using Large Neighbourhood Search
Krishna Kalavadia, Shamak Dutta, Yash Vardhan Pant +1
Autonomous navigation often requires the simultaneous optimization of multiple objectives. The most common approach scalarizes these into a single cost function using a weighted su…
Hierarchical Informative Path Planning via Graph Guidance and Trajectory Optimization
Avraiem Iskandar, Shamak Dutta, Kevin Murrant +2
We study informative path planning (IPP) with travel budgets in cluttered environments, where an agent collects measurements of a latent field modeled as a Gaussian process (GP) to…
DiffFP: Learning Behaviors from Scratch via Diffusion-based Fictitious Play
Akash Karthikeyan, Yash Vardhan Pant
Self-play reinforcement learning has demonstrated significant success in learning complex strategic and interactive behaviors in competitive multi-agent games. However, achieving s…
SAC-MoE: Reinforcement Learning with Mixture-of-Experts for Control of Hybrid Dynamical Systems with Uncertainty
Leroy D'Souza, Akash Karthikeyan, Yash Vardhan Pant +1
Hybrid dynamical systems result from the interaction of continuous-variable dynamics with discrete events and encompass various systems such as legged robots, vehicles and aircraft…
Tractable Stochastic Hybrid Model Predictive Control using Gaussian Processes for Repetitive Tasks in Unseen Environments
Leroy D'Souza, Yash Vardhan Pant, Sebastian Fischmeister
Improving the predictive accuracy of a dynamics model is crucial to obtaining good control performance and safety from Model Predictive Controllers (MPC). One approach involves lea…