Encoderless Gimbal Calibration of Dynamic Multi-Camera Clusters

TL;DR

This paper introduces an encoderless calibration method for dynamic multi-camera clusters mounted on gimbals, enabling simultaneous estimation of kinematic parameters and joint angles without joint sensors, validated through simulations and UAV experiments.

Contribution

It presents a novel encoderless calibration approach for DCCs, integrating online joint angle estimation with visual-inertial odometry, applicable to off-the-shelf gimbal systems.

Findings

Successful calibration in simulation and real-world tests

Maintains localization accuracy comparable to static camera setups

Enables online joint angle estimation without encoders

Abstract

Dynamic Camera Clusters (DCCs) are multi-camera systems where one or more cameras are mounted on actuated mechanisms such as a gimbal. Existing methods for DCC calibration rely on joint angle measurements to resolve the time-varying transformation between the dynamic and static camera. This information is usually provided by motor encoders, however, joint angle measurements are not always readily available on off-the-shelf mechanisms. In this paper, we present an encoderless approach for DCC calibration which simultaneously estimates the kinematic parameters of the transformation chain as well as the unknown joint angles. We also demonstrate the integration of an encoderless gimbal mechanism with a state-of-the art VIO algorithm, and show the extensions required in order to perform simultaneous online estimation of the joint angles and vehicle localization state. The proposed calibration approach is validated both in simulation and on a physical DCC composed of a 2-DOF gimbal mounted on a UAV. Finally, we show the experimental results of the calibrated mechanism integrated into the OKVIS VIO package, and demonstrate successful online joint angle estimation while maintaining localization accuracy that is comparable to a standard static multi-camera configuration.