Cooperative Transportation Robot System Using Risk-Sensitive Stochastic Control

Abstract

We propose a method to determine control input on the basis of minimizing the risk-sensitive cost function and show the results of an experiment in which the method was applied to a cooperative transportation robot system that we have developed. In the robot system, two robots hold a work object to transport without an external fixing device. The mechanism yields the force interaction between the robots and the object, which results in unexpected random errors in transportation. We add a stochastic term to the system model to describe such errors and solve the stochastic differential equation numerically to estimate the cost function. Utilizing the risk-sensitive cost function enables us to find the control input that balances efficiency and safety. The experimental results revealed that the chance of a robot colliding with an obstacle during transportation decreased from 90% to 7% compared with the optimal control.