In this work, we demonstrate the application of a simple first-order Tay...
In this paper, we address the trajectory planning problem in uncertain
n...
Text embeddings are useful features for several NLP applications, such a...
We consider the motion planning problem for stochastic nonlinear systems...
In this paper, we consider the closed-loop control problem of nonlinear
...
Many practical applications of robotics require systems that can operate...
In transportation networks, where traffic lights have traditionally been...
We address the risk bounded trajectory optimization problem of stochasti...
Teachers often conduct surveys in order to collect data from a predefine...
In this paper, we address the real-time risk-bounded safety verification...
Risk-bounded motion planning is an important yet difficult problem for
s...
We propose Automatic Curricula via Expert Demonstrations (ACED), a
reinf...
In this paper, we address the trajectory planning problem in uncertain
n...
Planning in hybrid systems with both discrete and continuous control
var...
We present a scalable and effective multi-agent safe motion planner that...
In order to provide adaptive and user-friendly solutions to robotic
mani...
This paper presents fast non-sampling based methods to assess the risk o...
This document describes the aggregation and anonymization process applie...
Chance-constrained motion planning requires uncertainty in dynamics to b...
Real-world environments are inherently uncertain, and to operate safely ...
To operate reactively in uncertain environments, robots need to be able ...
Agent behavior is arguably the greatest source of uncertainty in traject...
In planning and scheduling, solving problems with both state and tempora...
In temporal planning, many different temporal network formalisms are use...
This paper introduces Probabilistic Chekov (p-Chekov), a chance-constrai...
We present an evaluation of several representative sampling-based and
op...
The problem of scheduling under resource constraints is widely applicabl...
This work presents Drake, a dynamic executive for temporal plans with ch...