16 citations · 28 across the 4 of their papers we have counts for
5 papers
Model Predictive Inferential Control of Neural State-Space Models for Autonomous Vehicle Motion Planning
Iman Askari, Ali Vaziri, Xuemin Tu +2
Model predictive control (MPC) has proven useful in enabling safe and optimal motion planning for autonomous vehicles. In this paper, we investigate how to achieve MPC-based motion…
Model Predictive Control of Nonlinear Latent Force Models: A Scenario-Based Approach
Thomas Woodruff, Iman Askari, Guanghui Wang +1
Control of nonlinear uncertain systems is a common challenge in the robotics field. Nonlinear latent force models, which incorporate latent uncertainty characterized as Gaussian pr…
Sampling-Based Nonlinear MPC of Neural Network Dynamics with Application to Autonomous Vehicle Motion Planning
Iman Askari, Babak Badnava, Thomas Woodruff +2
Control of machine learning models has emerged as an important paradigm for a broad range of robotics applications. In this paper, we present a sampling-based nonlinear model predi…
Nonlinear Model Predictive Control Based on Constraint-Aware Particle Filtering/Smoothing
Iman Askari, Shen Zeng, Huazhen Fang
Nonlinear model predictive control (NMPC) has gained widespread use in many applications. Its formulation traditionally involves repetitively solving a nonlinear constrained optimi…
Implicit Particle Filtering via a Bank of Nonlinear Kalman Filters
Iman Askari, Mulugeta A. Haile, Xuemin Tu +1
The implicit particle filter seeks to mitigate particle degeneracy by identifying particles in the target distribution's high-probability regions. This study is motivated by the ne…