61 citations · 243 across the 64 of their papers we have counts for
5 papers · 2 filters
Active Learning with Dual Model Predictive Path-Integral Control for Interaction-Aware Autonomous Highway On-ramp Merging
Jacob Knaup, Jovin D'sa, Behdad Chalaki +4
Merging into dense highway traffic for an autonomous vehicle is a complex decision-making task, wherein the vehicle must identify a potential gap and coordinate with surrounding hu…
Kinodynamic FMT* with Dimensionality Reduction Heuristics and Neural Network Controllers
Dongliang Zheng, Panagiotis Tsiotras
This paper proposes a new sampling-based kinodynamic motion planning algorithm, called FMT*PFF, for nonlinear systems. It exploits the novel idea of dimensionality reduction using…
IBBT: Informed Batch Belief Trees for Motion Planning Under Uncertainty
Dongliang Zheng, Panagiotis Tsiotras
In this work, we propose the Informed Batch Belief Trees (IBBT) algorithm for motion planning under motion and sensing uncertainties. The original stochastic motion planning proble…
Non-Trivial Query Sampling For Efficient Learning To Plan
Sagar Suhas Joshi, Panagiotis Tsiotras
In recent years, learning-based approaches have revolutionized motion planning. The data generation process for these methods involves caching a large number of high quality paths…
Shield Model Predictive Path Integral: A Computationally Efficient Robust MPC Approach Using Control Barrier Functions
Ji Yin, Charles Dawson, Chuchu Fan +1
Model Predictive Path Integral (MPPI) control is a type of sampling-based model predictive control that simulates thousands of trajectories and uses these trajectories to synthesiz…