Recent advances in metric, semantic, and topological mapping have equipp...
Reliable autonomous navigation requires adapting the control policy of a...
Developing efficient solutions for inference problems in intelligent sen...
The graph identification problem consists of discovering the interaction...
This paper develops methods for proving Lyapunov stability of dynamical
...
This paper proposes a novel model-based policy gradient algorithm for
tr...
Incorporating prior knowledge of physics laws and structural properties ...
This paper considers enforcing safety and stability of dynamical systems...
This paper proposes a method for learning continuous control policies fo...
In this paper, we develop an approach that enables autonomous robots to ...
This paper presents LEMURS, an algorithm for learning scalable multi-rob...
This paper considers the problem of safely coordinating a team of
sensor...
Stability and safety are critical properties for successful deployment o...
Active Simultaneous Localization and Mapping (SLAM) is the problem of
pl...
This paper considers learning robot locomotion and manipulation tasks fr...
This paper considers outdoor terrain mapping using RGB images obtained f...
The problem of active mapping aims to plan an informative sequence of se...
This paper considers safe control synthesis for dynamical systems in the...
Most existing multi-agent reinforcement learning (MARL) methods are limi...
In real-world robotics applications, accurate models of robot dynamics a...
Safe autonomous navigation in unknown environments is an important probl...
The demand for robot exploration in unstructured and unknown environment...
This paper proposes a novel active Simultaneous Localization and Mapping...
Multi-agent mapping is a fundamentally important capability for autonomo...
Fast adaptive control is a critical component for reliable robot autonom...
Autonomous systems need to understand the semantics and geometry of thei...
Neural networks that map 3D coordinates to signed distance function (SDF...
Accurate models of robot dynamics are critical for safe and stable contr...
We develop an online probabilistic metric-semantic mapping approach for
...
This paper considers online object-level mapping using partial point-clo...
This paper presents a method for learning logical task specifications an...
This paper develops iterative Covariance Regulation (iCR), a novel
metho...
This paper focuses on pose registration of different object instances fr...
This paper focuses on building semantic maps, containing object poses an...
This paper considers the problem of planning trajectories for a team of
...
This paper aims to mitigate straggler effects in synchronous distributed...
This paper addresses outdoor terrain mapping using overhead images obtai...
Many robot applications call for autonomous exploration and mapping of
u...
This paper focuses on inverse reinforcement learning for autonomous
navi...
This paper focuses on learning a model of system dynamics online while
s...
Control barrier functions are widely used to enforce safety properties i...
This paper focuses on online occupancy mapping and real-time collision
c...
Introducing object-level semantic information into simultaneous localiza...
This paper focuses on inverse reinforcement learning (IRL) for autonomou...
This paper considers the problem of safe autonomous navigation in unknow...
This paper focuses on inverse reinforcement learning (IRL) to enable saf...
This paper considers the problem of fast and safe autonomous navigation ...
This paper focuses on real-time occupancy mapping and collision checking...
This paper focuses on learning a model of system dynamics online while
s...
This work presents an explicit-implicit procedure that combines an offli...