This paper introduces a new dual monocular visualinertial odometry (dual-VIO) strategy for a mobile manipulator operating under dynamic locomotion, i.e. coordinated movement involving both the base platform and the manipulator arm. Our approach has been motivated by challenges arising from inaccurate estimation due to coupled excitation when the mobile manipulator is engaged in dynamic locomotion in cluttered environments. The technique maintains two independent monocular VIO modules, with one at the mobile base and the other at the end-effector (EE), which are tightly coupled at the low level of the factor graph. The proposed method treats each monocular VIO with respect to each other as a positional anchor through arm-kinematics. These anchor points provide a soft geometric constraint during the VIO pose optimization. This allows us to stabilize both estimators in case of instability of one estimator in highly dynamic locomotions. The performance of our approach has been demonstrated through extensive experimental testing with a mobile manipulator tested in comparison to running dual VINS-Mono in parallel. We envision that our method can also provide a foundation towards active-SLAM (ASLAM) with a new perspective on multi-VIO fusion and system redundancy.

翻译：本文针对在动态运动（即涉及基座平台和机械臂的协调运动）下操作的移动机械臂，提出了一种新的双单目视觉惯性里程计（双VIO）策略。我们的方法源于移动机械臂在杂乱环境中进行动态运动时，由于耦合激励导致估计不准确所带来的挑战。该技术维持两个独立的单目VIO模块，一个位于移动基座，另一个位于末端执行器（EE），二者在因子图的底层进行紧耦合。所提出的方法通过手臂运动学，将每个单目VIO相对于另一个视为一个位置锚点。这些锚点在VIO位姿优化过程中提供了软几何约束。这使得在一个估计器在高度动态运动中不稳定时，我们能够稳定两个估计器。我们通过广泛的实验测试，与并行运行双VINS-Mono进行比较，验证了所提方法的性能。我们设想，我们的方法也能为主动SLAM（ASLAM）提供基础，并为多VIO融合与系统冗余提供新的视角。