SUMMARY

Cranes are used to lift and move large objects in a wide variety of applications including constructions sites, ports, and manufacturing facilities. If the load to be moved is too long or heavy for a single crane, two cranes must work in unison to achieve the desired outcome. In a factory setting this can be accomplished using two trolleys running along the same bridge forming a Dual Hoist crane. Using two hoists not only increases lifting capacity, it also increases stability of the payload over traditional single hoist configurations. This research takes advantage of that increased stability and explores a novel application for dual hoist cranes, suspending a robot arm from the hooks. This increases the workspace of the robot to the entirety of the space covered by the crane, opening up numerous applications not possible with the robot alone. In order to better understand and characterize the dynamics of the system, a numerical model was developed and tested against the physical system to confirm its validity.

Integration of a vision sensor mounted on the robot was also explored. The ASUS Xtion was chosen due to its capabilities as both a vision and depth sensor. The uses of such a sensor range from inspection to obstacle detection and avoidance. The quality of the data returned from the sensor was found to be dependent upon the magnitude of the residual oscillation of the robot crane system. These fluctuations in accuracy were explored and characterized and input shaping was used to decrease residual vibration thereby increasing data quality.

Finally, two possible uses of the system were explored, painting and sandblasting. The efficiency of a factory equipped with this system can be drastically increased at relatively low cost by automating manual tasks such as these.