Control Strategy of Stable Climbing Mechanics for Gecko-Inspired Robot on Vertical Arc Surface

With the rapid development of global industry, the storage capacity of oil tanks and wind turbine towers worldwide is gradually increasing and with it the problem of their maintenance: how to achieve a stable attachment of maintenance equipment to such vertical arcs? Wall-climbing robots are the ideal delivery platform due to their interface bonding capabilities. However, the robot is susceptible to the curvature of the curved surface. If the contact between its attachments and the crawling surface is inadequate, the closed chain system formed by the stance phase is unable to resist the force impact from the sticky release, and the risk of the robot destabilizing and tipping over is great. To improve the robot's adaptive capacity and anti-disturbance capability, this paper proposes an adaptive external force-softening motion strategy for the limbs of the inner and outer curved stance phases to ensure the stability of the robot body. The foot end motion is orthogonally decoupled into the forward direction and the arc surface fitting direction, and the stance phase adopts a virtual mass-damping control model to realize the spring cushioning behavior of the system during the forward motion. The experimental results show that the algorithm proposed in this paper can effectively improve the stability of the robot in the process of vertical arc crawling and avoid the phenomenon of unstable fall.