Mitigating Dynamic Tip-Over during Mobile Crane Slewing using Input Shaping

TL;DR

This paper introduces an input shaping method for mobile crane slewing that reduces payload swing and enhances safety without sacrificing speed, significantly improving operational efficiency and safety margins.

Contribution

It proposes a simple input shaping technique requiring only rope length information to prevent tip-over during rapid crane slewing, without needing detailed dynamic models.

Findings

Reduces residual payload swing by 18%.

Enables 38% faster slewing speeds without tip-over.

Decreases collision potential by 82%.

Abstract

Payload swing during rapid slewing of mobile cranes poses a safety risk, as it generates overturning moments that can lead to tip-over accidents of mobile cranes. Currently, to limit the risk of tip-over, mobile crane operators are forced to either reduce the slewing speed (which lowers productivity) or reduce the load being carried to reduce the induced moments. Both of these approaches reduce productivity. This paper seeks to enable rapid slewing without compromising safety by applying input shaping to the crane-slewing commands generated by the operator. A key advantage of this approach is that the input shaper requires only the information about the rope length, and does not require detailed mobile crane dynamics. Simulations and experiments show that the proposed method reduces residual payload swing and enables significantly higher slewing speeds without tip over, reducing slewing completion time by at least 38% compared to unshaped control. Human control with input shaping improves task completion time by 13%, reduces the peak swing by 18%, and reduces the potential of collisions by 82% when compared to unshaped control. Moreover, shaped control with a human had no tip-over, whereas large swing led to tip-over without input shaping. Thereby, the proposed method substantially recovers the operational-safety envelope of mobile cranes (designed to avoid tip-over using static analysis) that would otherwise be lost in dynamic conditions. Videos and demonstrations are available at https://youtu.be/dVy3bbIhrBU.