Behavior-Based Door Opening with Equilibrium Point Control

Within this paper we present a set of behaviors that enable a mobile manipulator to reliably open a variety of doors. After a user designates a location within 20cm of the door handle, the robot autonomously locates the door handle using a tilting laser range finder, approaches the handle using its omnidirectional base, reaches out to haptically find the door, makes contact with the handle, twists it, and pushes open the door. The robot uses equilibrium point control for all arm motions. Our implementation uses a 7 DoF anthropomorphic arm with series elastic actuators (SEAs). For our control scheme, each SEA applies a gravity compensating torque plus a torque from a simulated, torsional, viscoelastic spring. Each virtual spring has constant stiffness and damping, and a variable equilibrium point. The behaviors use inverse kinematics to generate trajectories for these joint-space equilibrium points that correspond with Cartesian equilibrium point trajectories for the end effector. With 43 trials and 8 different doors, we show that these compliant trajectories enable the robot to robustly reach out to make contact with doors (100%), operate door handles (96.9%), and push doors open (100%). The complete system including perception and navigation succeeded with unlocked doors in 28 out of 32 trials (87.5%) and locked doors in 8 out of 8 trials (100%). Through 157 trials with a single door, we empirically show that our method for door handle twisting reduces interaction forces and is robust to variations in arm stiffness, the end effector trajectory, and the friction between the end effector and the handle.