Autonomous robotic systems, such as quadrotors, are susceptible to actua...
Before autonomous systems can be deployed in safety-critical application...
Ensuring safety and meeting temporal specifications are critical challen...
Tasks for autonomous robotic systems commonly require stabilization to a...
Hybrid systems are prevalent in robotics. However, ensuring the stabilit...
Large-scale self-supervised models have recently revolutionized our abil...
Model Predictive Path Integral (MPPI) control is a type of sampling-base...
Learning-based methods have shown promising performance for accelerating...
Autonomous systems with uncertainties are prevalent in robotics. However...
To navigate complex environments, robots must increasingly use
high-dime...
Density of the reachable states can help understand the risk of
safety-c...
There is a growing need for computational tools to automatically design ...
Multi-robot assembly systems are becoming increasingly appealing in
manu...
Signal temporal logic (STL) provides a powerful, flexible framework for
...
Learning-enabled control systems have demonstrated impressive empirical
...
We tackle the challenging problem of multi-agent cooperative motion plan...
Control certificates based on barrier functions have been a powerful too...
Many robotic tasks require high-dimensional sensors such as cameras and ...
This paper presents a theoretical overview of a Neural Contraction Metri...
State density distribution, in contrast to worst-case reachability, can ...
Safety and stability are common requirements for robotic control systems...
Reactive and safe agent modelings are important for nowadays traffic
sim...
We study constrained reinforcement learning (CRL) from a novel perspecti...
In this paper, we consider the problem of using a robot to explore an
en...
Planning in hybrid systems with both discrete and continuous control
var...
We study the multi-agent safe control problem where agents should avoid
...
We present a scalable and effective multi-agent safe motion planner that...
In this paper, we solve the problem of finding a certified control polic...
Motion planning in environments with multiple agents is critical to many...
We show that symmetry transformations and caching can enable scalable, a...
For many structured learning tasks, the data annotation process is compl...
Annotating temporal relations (TempRel) between events described in natu...