A snake-like robot can move in not only the dry ground but also various viscous environments of water, mud, and clay by exhibiting undulating motions. To construct the numerical model including the fluid–structure interaction for the snake-like robot under the above-mentioned environments, the added mass and drag coefficients for the snake-like robot must be identified via experimentation because they depend on the shape of the body, the roughness of the skin, and the viscosity of the fluid. In this work, firstly, we performed experiments in which a snake-like robot of eight links exhibits swimming motions in three fluids of different kinematic viscosities, and we measured its joint positions during swimming. Subsequently, we proposed a numerical model of the snake-like robot swimming in fluids with a wide range of viscosities, and the identification method of some unknown fluid force parameters using an unscented Kalman filter. After that, we identified the unknown added mass and drag coefficients for the fluid force acting on the snake-like robot by using the proposed method. Then, we clarified that the appropriate drag model is the inertia drag model for water with small viscosity and the viscous drag model for oil which is a highly viscous fluid. Moreover, we confirmed that the undulation increased the tangential drag force along the body by 1.4 times. The position and velocity of the center of gravity of the snake-like robot, calculated using the numerical models, also agreed with the experimental results.

蛇形机器人不仅可以在干燥的地面上移动，还可以通过表现出起伏的运动在水、泥、粘土等各种粘性环境中移动。为了构建包含上述环境下蛇形机器人流固耦合的数值模型，蛇形机器人的附加质量和阻力系数必须通过实验确定，因为它们取决于身体的形状、皮肤的粗糙度和流体的粘度。在这项工作中，我们首先进行了一个实验，其中一个八连杆的蛇形机器人在三种不同运动粘度的流体中表现出游泳运动，并在游泳过程中测量了其关节位置。随后，我们提出了蛇形机器人在具有广泛粘度的流体中游泳的数值模型，以及使用无迹卡尔曼滤波器识别一些未知流体力参数的方法。之后，我们使用所提出的方法确定了作用在蛇形机器人上的流体力的未知附加质量和阻力系数。然后，我们明确了合适的阻力模型是低粘度水的惯性阻力模型和高粘度流体油的粘性阻力模型。此外，我们确认波动使沿身体的切向阻力增加了 1.4 倍。使用数值模型计算得到的蛇形机器人重心位置和速度也与实验结果一致。我们使用所提出的方法确定了作用在蛇形机器人上的流体力的未知附加质量和阻力系数。然后，我们明确了合适的阻力模型是低粘度水的惯性阻力模型和高粘度流体油的粘性阻力模型。此外，我们确认波动使沿身体的切向阻力增加了 1.4 倍。使用数值模型计算得到的蛇形机器人重心位置和速度也与实验结果一致。我们使用所提出的方法确定了作用在蛇形机器人上的流体力的未知附加质量和阻力系数。然后，我们明确了合适的阻力模型是低粘度水的惯性阻力模型和高粘度流体油的粘性阻力模型。此外，我们确认波动使沿身体的切向阻力增加了 1.4 倍。使用数值模型计算得到的蛇形机器人重心位置和速度也与实验结果一致。我们证实，起伏使沿身体的切向阻力增加了 1.4 倍。使用数值模型计算得到的蛇形机器人重心位置和速度也与实验结果一致。我们证实，起伏使沿身体的切向阻力增加了 1.4 倍。使用数值模型计算得到的蛇形机器人重心位置和速度也与实验结果一致。