139 citations · 987 across the 58 of their papers we have counts for
58 papers
A Sliding Window Filter on the Galilean Group for Consistent Aided Inertial Navigation with Unknown Measurement Delays
Jonathan Kelly
We study aided inertial navigation when the aiding sensor measurements are subject to an unknown constant delay. The goal is to estimate the delay and navigation state jointly so t…
Lost in Time? Continuous Symmetry and Identifiability in Aided Inertial Navigation with Unknown Measurement Delays
Jonathan Kelly, Phone Thiha Kyaw, Matthew Giamou
In many multisensor systems, measurements from different sensors are subject to unknown relative time delays. Accurate state estimation requires that delays be accounted for and, w…
On the Identifiability of Aided Inertial Navigation Under Measurement Delays: A Geometric Approach
Jonathan Kelly
In aided inertial navigation, measurements from different sensors are often subject to unknown relative time delays. Consider a single aiding sensor whose measurements have an unkn…
Euclidean Equivariant Models for Generative Graphical Inverse Kinematics
Oliver Limoyo, Filip Marić, Matthew Giamou +3
Quickly and reliably finding accurate inverse kinematics (IK) solutions remains a challenging problem for robotic manipulation. Existing numerical solvers typically produce a singl…
Recovery Policies for Safe Exploration of Lunar Permanently Shadowed Regions by a Solar-Powered Rover
Olivier Lamarre, Shantanu Malhotra, Jonathan Kelly
The success of a multi-kilometre drive by a solar-powered rover at the lunar south pole depends upon careful planning in space and time due to highly dynamic solar illumination con…
CIDGIKc: Distance-Geometric Inverse Kinematics for Continuum Robots
Hanna Jiamei Zhang, Matthew Giamou, Filip Marić +2
The small size, high dexterity, and intrinsic compliance of continuum robots (CRs) make them well suited for constrained environments. Solving the inverse kinematics (IK), that is…
aUToLights: A Robust Multi-Camera Traffic Light Detection and Tracking System
Sean Wu, Nicole Amenta, Jiachen Zhou +2
Following four successful years in the SAE AutoDrive Challenge Series I, the University of Toronto is participating in the Series II competition to develop a Level 4 autonomous pas…
The Sum of Its Parts: Visual Part Segmentation for Inertial Parameter Identification of Manipulated Objects
Philippe Nadeau, Matthew Giamou, Jonathan Kelly
To operate safely and efficiently alongside human workers, collaborative robots (cobots) require the ability to quickly understand the dynamics of manipulated objects. However, tra…
Extrinsic Calibration of 2D Millimetre-Wavelength Radar Pairs Using Ego-Velocity Estimates
Qilong Cheng, Emmett Wise, Jonathan Kelly
Correct radar data fusion depends on knowledge of the spatial transform between sensor pairs. Current methods for determining this transform operate by aligning identifiable featur…
Learning from Guided Play: Improving Exploration for Adversarial Imitation Learning with Simple Auxiliary Tasks
Trevor Ablett, Bryan Chan, Jonathan Kelly
Adversarial imitation learning (AIL) has become a popular alternative to supervised imitation learning that reduces the distribution shift suffered by the latter. However, AIL requ…
Spatiotemporal Calibration of 3D Millimetre-Wavelength Radar-Camera Pairs
Emmett Wise, Qilong Cheng, Jonathan Kelly
Autonomous vehicles (AVs) fuse data from multiple sensors and sensing modalities to impart a measure of robustness when operating in adverse conditions. Radars and cameras are popu…
Generative Graphical Inverse Kinematics
Oliver Limoyo, Filip Marić, Matthew Giamou +3
Quickly and reliably finding accurate inverse kinematics (IK) solutions remains a challenging problem for many robot manipulators. Existing numerical solvers are broadly applicable…
LaTeRF: Label and Text Driven Object Radiance Fields
Ashkan Mirzaei, Yash Kant, Jonathan Kelly +1
Obtaining 3D object representations is important for creating photo-realistic simulations and for collecting AR and VR assets. Neural fields have shown their effectiveness in learn…
Learning Sequential Latent Variable Models from Multimodal Time Series Data
Oliver Limoyo, Trevor Ablett, Jonathan Kelly
Sequential modelling of high-dimensional data is an important problem that appears in many domains including model-based reinforcement learning and dynamics identification for cont…
A Self-Supervised, Differentiable Kalman Filter for Uncertainty-Aware Visual-Inertial Odometry
Brandon Wagstaff, Emmett Wise, Jonathan Kelly
Visual-inertial odometry (VIO) systems traditionally rely on filtering or optimization-based techniques for egomotion estimation. While these methods are accurate under nominal con…
Fast Object Inertial Parameter Identification for Collaborative Robots
Philippe Nadeau, Matthew Giamou, Jonathan Kelly
Collaborative robots (cobots) are machines designed to work safely alongside people in human-centric environments. Providing cobots with the ability to quickly infer the inertial p…
Learning to Detect Slip with Barometric Tactile Sensors and a Temporal Convolutional Neural Network
Abhinav Grover, Philippe Nadeau, Christopher Grebe +1
The ability to perceive object slip via tactile feedback enables humans to accomplish complex manipulation tasks including maintaining a stable grasp. Despite the utility of tactil…
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning
Trevor Ablett, Bryan Chan, Jonathan Kelly
Effective exploration continues to be a significant challenge that prevents the deployment of reinforcement learning for many physical systems. This is particularly true for system…
Observability-Aware Trajectory Optimization: Theory, Viability, and State of the Art
Christopher Grebe, Emmett Wise, Jonathan Kelly
Ideally, robots should move in ways that maximize the knowledge gained about the state of both their internal system and the external operating environment. Trajectory design is a…
Convex Iteration for Distance-Geometric Inverse Kinematics
Matthew Giamou, Filip Marić, David M. Rosen +4
Inverse kinematics (IK) is the problem of finding robot joint configurations that satisfy constraints on the position or pose of one or more end-effectors. For robots with redundan…
Riemannian Optimization for Distance-Geometric Inverse Kinematics
Filip Marić, Matthew Giamou, Adam W. Hall +3
Solving the inverse kinematics problem is a fundamental challenge in motion planning, control, and calibration for articulated robots. Kinematic models for these robots are typical…
On the Coupling of Depth and Egomotion Networks for Self-Supervised Structure from Motion
Brandon Wagstaff, Valentin Peretroukhin, Jonathan Kelly
Structure from motion (SfM) has recently been formulated as a self-supervised learning problem, where neural network models of depth and egomotion are learned jointly through view…
A Question of Time: Revisiting the Use of Recursive Filtering for Temporal Calibration of Multisensor Systems
Jonathan Kelly, Christopher Grebe, Matthew Giamou
We examine the problem of time delay estimation, or temporal calibration, in the context of multisensor data fusion. Differences in processing intervals and other factors typically…
Seeing All the Angles: Learning Multiview Manipulation Policies for Contact-Rich Tasks from Demonstrations
Trevor Ablett, Yifan Zhai, Jonathan Kelly
Learned visuomotor policies have shown considerable success as an alternative to traditional, hand-crafted frameworks for robotic manipulation. Surprisingly, an extension of these…