Learning-based controllers have demonstrated superior performance compar...
3D object-level mapping is a fundamental problem in robotics, which is
e...
Range-only (RO) pose estimation involves determining a robot's pose over...
Shared benchmark problems have historically been a fundamental driver of...
Open-sourcing research publications is a key enabler for the reproducibi...
Ultra-wideband (UWB) time difference of arrival(TDOA)-based localization...
In this paper we investigate the effect of the unpredictability of
surro...
Learning-based optimal control algorithms control unknown systems using ...
Simultaneous localization and mapping (SLAM) in slowly varying scenes is...
We consider a nonprehensile manipulation task in which a mobile manipula...
We present the first controller for quasistatic robotic planar pushing w...
Range-only (RO) localization involves determining the position of a mobi...
6D Object pose estimation is a fundamental component in robotics enablin...
This paper presents a scalable online algorithm to generate safe and
kin...
In this study, we leverage the deliberate and systematic fault-injection...
Autonomous mobile robots, including unmanned aerial vehicles (UAVs), hav...
Maintaining an up-to-date map to reflect recent changes in the scene is ...
Ultra-wideband (UWB) time difference of arrival (TDOA)-based localizatio...
In this work, we consider the problem of designing a safety filter for a...
This paper presents an ultra-wideband (UWB) time-difference-of-arrival (...
Radar is a rich sensing modality that is a compelling alternative to lid...
The Boreas dataset was collected by driving a repeated route over the co...
As robots venture into the real world, they are subject to unmodeled dyn...
In this work we address the problem of performing a repetitive task when...
Current control design for fast vision-based flight tends to rely on
hig...
In recent years, reinforcement learning and learning-based control – as ...
The last half-decade has seen a steep rise in the number of contribution...
The combination of ultrawideband (UWB) radios and inertial measurement u...
This paper presents a radar odometry method that combines probabilistic
...
In self-driving, standalone GPS is generally considered to have insuffic...
Robotic simulators are crucial for academic research and education as we...
Accurate indoor localization is a crucial enabling technology for many
r...
In order to tackle the challenge of unfavorable weather conditions such ...
In the robotics literature, experience transfer has been proposed in
dif...
The SAE AutoDrive Challenge is a three-year collegiate competition to de...
In the robotics literature, different knowledge transfer approaches have...
We present parameter learning in a Gaussian variational inference settin...
Accurate indoor localization is a crucial enabling technology for many
r...
Mobile manipulators consist of a mobile platform equipped with one or mo...
Deep neural networks (DNNs) have emerged as a popular mathematical tool ...
We present a distributed model predictive control (DMPC) algorithm to
ge...
The control of a quadrotor is typically split into two subsequent proble...
The University of Toronto is one of eight teams competing in the SAE
Aut...
We present a hierarchical framework for motion planning of a large colle...
We present a modular framework for solving a motion planning problem amo...
In this paper, we propose an online learning approach that enables the
i...
Bayesian optimization (BO) based on Gaussian process models is a powerfu...
The SAE AutoDrive Challenge is a three-year competition to develop a Lev...
We present a control method for improved repetitive path following for a...
This paper aims to design quadrotor swarm performances, where the swarm ...