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A Novel Identification Methodology for the Coordinate Relationship between a 3D Vision System and a Legged Robot

机译：一种新型识别方法用于3D视觉系统和腿式机器人之间的坐标关系

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摘要

Coordinate identification between vision systems and robots is quite a challenging issue in the field of intelligent robotic applications, involving steps such as perceiving the immediate environment, building the terrain map and planning the locomotion automatically. It is now well established that current identification methods have non-negligible limitations such as a difficult feature matching, the requirement of external tools and the intervention of multiple people. In this paper, we propose a novel methodology to identify the geometric parameters of 3D vision systems mounted on robots without involving other people or additional equipment. In particular, our method focuses on legged robots which have complex body structures and excellent locomotion ability compared to their wheeled/tracked counterparts. The parameters can be identified only by moving robots on a relatively flat ground. Concretely, an estimation approach is provided to calculate the ground plane. In addition, the relationship between the robot and the ground is modeled. The parameters are obtained by formulating the identification problem as an optimization problem. The methodology is integrated on a legged robot called “Octopus”, which can traverse through rough terrains with high stability after obtaining the identification parameters of its mounted vision system using the proposed method. Diverse experiments in different environments demonstrate our novel method is accurate and robust.
机译：在智能机器人应用领域，视觉系统与机器人之间的坐标识别是一个极具挑战性的问题，涉及诸如感知周围环境，构建地形图和自动规划运动等步骤。现在已经很好地确定，当前的识别方法具有不可忽略的局限性，例如困难的特征匹配，对外部工具的需求以及多人的干预。在本文中，我们提出了一种新颖的方法来识别安装在机器人上的3D视觉系统的几何参数，而无需其他人或其他设备的参与。特别是，我们的方法着重于腿式机器人，该机器人与轮式/履带式对等机器人相比具有复杂的身体结构和出色的运动能力。只能通过在相对平坦的地面上移动机器人来识别参数。具体而言，提供了一种估计方法来计算接地平面。此外，还对机器人与地面之间的关系进行了建模。通过将识别问题公式化为优化问题来获得参数。该方法集成在一个名为“章鱼”的有腿机器人上，该机器人在使用所提出的方法获得其安装的视觉系统的识别参数后，可以高稳定性地穿越崎rough的地形。在不同环境中进行的各种实验表明，我们的新方法准确而可靠。

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