This work presents a novel Learning Model Predictive Control (LMPC) stra...
We present two approaches to compute raceline trajectories for quadrotor...
We present a data-driven optimization approach for robotic controlled
de...
This paper presents a novel energy-efficient motion planning algorithm f...
This work presents a distributed algorithm for resolving cooperative
mul...
A distributed coordination method for solving multi-vehicle lane changes...
We present a novel method to address the problem of multi-vehicle confli...
We propose a Model Predictive Control (MPC) for collision avoidance betw...
We study a human-robot collaborative transportation task in presence of
...
In head-to-head racing, performing tightly constrained, but highly rewar...
The problem of multimodal intent and trajectory prediction for human-dri...
We propose a Stochastic MPC (SMPC) formulation for autonomous driving at...
We address the problem of finding the current position and heading angle...
First-order methods for quadratic optimization such as OSQP are widely u...
This article proposes a hierarchical learning architecture for safe
data...
In this paper, we propose a leader-follower hierarchical strategy for tw...
"Bubble Ball" is a game built on a 2D physics engine, where a finite set...
We present a hierarchical control approach for maneuvering an autonomous...
Playing the cup-and-ball game is an intriguing task for robotics researc...
This work presents a distributed method for multi-robot coordination bas...
We propose a control design method for linear time-invariant systems tha...
We investigate the problem of predicting driver behavior in parking lots...
We present a Model Predictive Control (MPC) strategy for unknown input-a...
We present a decentralized trajectory optimization scheme based on learn...
Advances in vehicular communication technologies are expected to facilit...
We propose an approach to design a Model Predictive Controller (MPC) for...
We present a hardware-in-the-loop (HIL) simulation setup for repeatable
...
In this paper, we propose a novel framework for approximating the explic...
Reinforcement learning (RL) for robotics is challenging due to the diffi...
As autonomous vehicles (AVs) inch closer to reality, a central requireme...
We present the design of a safe Adaptive Cruise Control (ACC) which uses...
We propose a map-aided vehicle localization method for GPS-denied
enviro...
This paper presents a novel method for reformulating non-differentiable
...