This paper addresses a new motion planning problem for mobile robots tas...
Fleets of unmanned robots can be beneficial for the long-term monitoring...
While ensuring stability for linear systems is well understood, it remai...
Several task and motion planning algorithms have been proposed recently ...
Deep neural networks (DNN) have become a common sensing modality in
auto...
Trajectory prediction is an integral component of modern autonomous syst...
This paper addresses a new semantic multi-robot planning problem in unce...
This paper presents a new approach to design verified compositions of Ne...
This paper addresses a safe planning and control problem for mobile robo...
In this paper we address mobile manipulation planning problems in the
pr...
This paper addresses the problem of learning control policies for mobile...
We develop an algorithm for the motion and task planning of a system
com...
Motion planning is a fundamental problem and focuses on finding control
...
This paper addresses the problem of active information gathering for
mul...
This paper proposes a novel highly scalable non-myopic planning algorith...
This paper addresses a multi-robot mission planning problem in uncertain...
This paper proposes a new reactive temporal logic planning algorithm for...
Complex manipulation tasks, such as rearrangement planning of numerous
o...
In this paper, we consider networks of static sensors with integrated se...
Deep neural network (DNN) models have proven to be vulnerable to adversa...
Reinforcement Learning (RL) has emerged as an efficient method of choice...
The majority of existing Linear Temporal Logic (LTL) planning methods re...
This paper proposes proposes a new highly scalable optimal control synth...
This paper considers the problem of distributed state estimation using
m...
In this paper, we present a control framework that allows magnetic micro...
In this paper, we develop a decentralized intermittent communication and...