41 citations · 213 across the 24 of their papers we have counts for
25 papers
Uncertainty in space, time, and motion on the special Galilean group
Jonathan Kelly, Matthew Giamou
Classical mechanics unfolds within absolute time and Euclidean space, yet our knowledge of where events occur, when they occur, and how motion evolves is inherently uncertain. The…
Certifiable Alignment of GNSS and Local Frames via Lagrangian Duality
Baoshan Song, Matthew Giamou, Penggao Yan +2
Estimating the absolute orientation of a local system relative to a global navigation satellite system (GNSS) reference often suffers from local minima and high dependency on satel…
A Certifably Correct Algorithm for Generalized Robot-World and Hand-Eye Calibration
Emmett Wise, Pushyami Kaveti, Qilong Chen +5
Automatic extrinsic sensor calibration is a fundamental problem for multi-sensor platforms. Reliable and general-purpose solutions should be computationally efficient, require few…
Towards Optimal Beacon Placement for Range-Aided Localization
Ethan Sequeira, Hussein Saad, Stephen Kelly +1
Range-based localization is ubiquitous: global navigation satellite systems (GNSS) power mobile phone-based navigation, and autonomous mobile robots can use range measurements from…
OASIS: Optimal Arrangements for Sensing in SLAM
Pushyami Kaveti, Matthew Giamou, Hanumant Singh +1
The number and arrangement of sensors on mobile robot dramatically influence its perception capabilities. Ensuring that sensors are mounted in a manner that enables accurate detect…
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…
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…
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…
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…
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…
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…
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…
Inverse Kinematics as Low-Rank Euclidean Distance Matrix Completion
Filip Marić, Matthew Giamou, Ivan Petrović +1
The majority of inverse kinematics (IK) algorithms search for solutions in a configuration space defined by joint angles. However, the kinematics of many robots can also be describ…
A Smooth Representation of Belief over SO(3) for Deep Rotation Learning with Uncertainty
Valentin Peretroukhin, Matthew Giamou, David M. Rosen +3
Accurate rotation estimation is at the heart of robot perception tasks such as visual odometry and object pose estimation. Deep neural networks have provided a new way to perform t…
Certifiably Optimal Monocular Hand-Eye Calibration
Emmett Wise, Matthew Giamou, Soroush Khoubyarian +2
Correct fusion of data from two sensors is not possible without an accurate estimate of their relative pose, which can be determined through the process of extrinsic calibration. W…
Inverse Kinematics for Serial Kinematic Chains via Sum of Squares Optimization
Filip Maric, Matthew Giamou, Soroush Khoubyarian +2
Inverse kinematics is a fundamental problem for articulated robots: fast and accurate algorithms are needed for translating task-related workspace constraints and goals into feasib…
Probabilistic Regression of Rotations using Quaternion Averaging and a Deep Multi-Headed Network
Valentin Peretroukhin, Brandon Wagstaff, Matthew Giamou +1
Accurate estimates of rotation are crucial to vision-based motion estimation in augmented reality and robotics. In this work, we present a method to extract probabilistic estimates…
Sparse Bounded Degree Sum of Squares Optimization for Certifiably Globally Optimal Rotation Averaging
Matthew Giamou, Filip Maric, Valentin Peretroukhin +1
Estimating unknown rotations from noisy measurements is an important step in SfM and other 3D vision tasks. Typically, local optimization methods susceptible to returning suboptima…
Certifiably Globally Optimal Extrinsic Calibration from Per-Sensor Egomotion
Matthew Giamou, Ziye Ma, Valentin Peretroukhin +1
We present a certifiably globally optimal algorithm for determining the extrinsic calibration between two sensors that are capable of producing independent egomotion estimates. Thi…
Near-Optimal Budgeted Data Exchange for Distributed Loop Closure Detection
Yulun Tian, Kasra Khosoussi, Matthew Giamou +2
Inter-robot loop closure detection is a core problem in collaborative SLAM (CSLAM). Establishing inter-robot loop closures is a resource-demanding process, during which robots must…
Talk Resource-Efficiently to Me: Optimal Communication Planning for Distributed Loop Closure Detection
Matthew Giamou, Kasra Khosoussi, Jonathan P. How
Due to the distributed nature of cooperative simultaneous localization and mapping (CSLAM), detecting inter-robot loop closures necessitates sharing sensory data with other robots.…
PROBE: Predictive Robust Estimation for Visual-Inertial Navigation
Valentin Peretroukhin, Lee Clement, Matthew Giamou +1
Navigation in unknown, chaotic environments continues to present a significant challenge for the robotics community. Lighting changes, self-similar textures, motion blur, and movin…
Entropy-Based Calibration of 2D Lidars to Egomotion Sensors
Jacob Lambert, Lee Clement, Matthew Giamou +1
This paper explores the use of an entropy-based technique for point cloud reconstruction with the goal of calibrating a lidar to a sensor capable of providing egomotion information…