Improving the safety of forklifts through automation of task execution

© 2016 Leng VongchanhForklift vehicles are used throughout the world, in many industries to move stock from location to location. Unfortunately these vehicles are prone to toppling, possibly causing stock damage, injuries and loss of income. There are fewer safety interventions applied to forklifts than would be expected of other wheeled vehicle, with the industry relying on operator training and experience to prevent accidents. This thesis proposes a method of measuring the toppling propensity, and a trajectory generation algorithm to allow the autonomous use of forklift vehicles. The zero moment point and a barycentric coordinate system will be used to measure the dynamic balance. The measure will allow analysis of forklift behaviour and may be used to provide information of the state of balance to the operator with the intent of aiding judgement and to improve accountability. The obtained dynamic balance measure will then be used as an inequality constraint during the construction of a non-holonomic trajectory. This will be used to ensure the trajectory complies with safe manoeuvring of the forklift vehicle. The autonomy of the vehicle will allow the operator to distance themselves from the vehicle, interacting only through high level decisions as opposed to low level handling of the vehicle, with the intent of removing the human element of error from the toppling problem. An analysis of forklift behaviour given differing loading scenarios will be discussed, with similar scenarios computationally simulated to produce sample trajectories of the new algorithm. The results are compared to intuitive notions of movement and to safety literature