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Title: Continuous-Time Spline Visual-Inertial Odometry
We propose a continuous-time spline-based formulation for visual-inertial odometry (VIO). Specifically, we model the poses as a cubic spline, whose temporal derivatives are used to synthesize linear acceleration and angular velocity, which are compared to the measurements from the inertial measurement unit (IMU) for optimal state estimation. The spline boundary conditions create constraints between the camera and the IMU, with which we formulate VIO as a constrained nonlinear optimization problem. Continuous-time pose representation makes it possible to address many VIO challenges, e.g., rolling shutter distortion and sensors that may lack synchronization. We conduct experiments on two publicly available datasets that demonstrate the state-of-the-art accuracy and real-time computational efficiency of our method.  more » « less
Award ID(s):
1637875
PAR ID:
10387638
Author(s) / Creator(s):
Date Published:
Journal Name:
Proiceedings of the 2022 International Conference on Robotics and Automation (ICRA)
Page Range / eLocation ID:
9492-9498
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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