Data-driven human skill evaluation for excavator operation

摘要

The construction field is increasingly adopting automation and manpower-saving technologies. However, automating all types of construction machinery is difficult because some operations require human skill and judgment-that is, professional skills-for realizing optimal work efficiency. However, the lack of competent professionals because of the decreasing and aging population in Japan is an emerging societal problem and is leading to concerns such as deterioration in workplace safety and difficulty in transferring professional skills. This study proposes human skill evaluation and assesses human skills through the application of control engineering. The human operator is analyzed as a nonlinear controller comprised of a proportional-integral-derivative (PID) controller and a PID parameter tuner. The parameters of this database-driven PID controller are tuned using data (i.e., reference signals, input signals, and output signals) obtained from operation. The proposed approach is experimentally demonstrated by applying it to the case of an excavator.