In this paper, WALK-VIO, a novel visual-inertial odometry (VIO) with walking-motion-adaptive leg kinematic constraints that change with body motion for localization of quadruped robots, is proposed. Quadruped robots primarily use VIO because they require fast localization for control and path planning. However, since quadruped robots are mainly used outdoors, extraneous features extracted from the sky or ground cause tracking failures. In addition, the quadruped robots' walking motion cause wobbling, which lowers the localization accuracy due to the camera and inertial measurement unit (IMU). To overcome these limitations, many researchers use VIO with leg kinematic constraints. However, since the quadruped robot's walking motion varies according to the controller, gait, quadruped robots' velocity, and so on, these factors should be considered in the process of adding leg kinematic constraints. We propose VIO that can be used regardless of walking motion by adjusting the leg kinematic constraint factor. In order to evaluate WALK-VIO, we create and publish datasets of quadruped robots that move with various types of walking motion in a simulation environment. In addition, we verified the validity of WALK-VIO through comparison with current state-of-the-art algorithms.
翻译:在本文中,提出了WALK-VIO,这是一部新型的视觉-肾上腺测量学(VIO),具有步行-动作适应性调整腿动因,随着四振机器人的定位运动而改变。四振机器人主要使用VIO,因为它们需要快速定位来控制和路径规划。然而,由于四振机器人主要在室外使用,从天空或地面提取的外体功能导致跟踪失败。此外,四振机器人的行进运动导致波动,由于摄像和惯性测量单位(IMU)而降低本地化精度。为了克服这些限制,许多研究人员使用VIO,具有腿动性限制。然而,四振机器人的行进动作因控制者、毛特、四振动机器人的速度而不同,因此,这些因素应该在增加腿运动制约的过程中加以考虑。我们提议可以使用VIO,通过调整腿运动和惯性约束因素(IMUMU)。为了比较WAL-OVI的动作有效性,在模拟过程中,通过机器人的四振动环境,我们可以使用VAL-OS-VS(V)的动动动动状态,在模拟中发布数据。