Chuande Liu, Bingtuan Gao, Chuang Yu and Adriana Tapus
Many work conditions require manipulators to open cabinet doors and then gain access to the desired workspace. However, after opening, the unlocked doors can easily close…
Abstract
Purpose
Many work conditions require manipulators to open cabinet doors and then gain access to the desired workspace. However, after opening, the unlocked doors can easily close, interrupt a task and potentially break the operating end-effectors. This paper aims to address a manipulator's behavior planning problem for responding to a dynamic workspace released by door opening.
Design/methodology/approach
A dynamic model of the restricted workspace released by an unlocked door is established. As a whole system to treat, the interactions between the workspace and robot are analyzed by using a partially observable Markov decision process. A self-protective policy decision executed as a belief tree is proposed. To respond to the policy, this study has designed three types of actions: stay on guard in the workspace, using an elbow joint to defense the door and linear escape out of the workspace for self-protection by observing collision risk levels to trigger them. Finally, this study proposes self-protective motion controllers based on risk time optimization to act to the planned actions.
Findings
The elbow defense could balance robotic safety and work efficiency by interrupting the end-effector's work and using the elbow joint to prevent the door-closing in an active collision way. Compared with the stay and escape action, the advantage of the elbow defense is having a predictable performance to quick callback the interrupted work after the risk was relieved.
Originality/value
This work provides guidance for the safe operation of a class of robot operations and the upgrade of motion planning.