Force and acceleration sensor fusion for compliant manipulation control in 6 degrees of freedom

Abstract

This paper focusses on sensor fusion in robotic manipulation: six-dimensional (6-D) force/torque signals and 6-D acceleration signals are used to extract forces and torques caused by inertia. As result, only forces and torques established by environmental contact(s) remain. Apart from an improvement of hybrid force/pose control behavior, an additional major benefit is that regular resetting/zeroing of force/torque sensors before free space/contact transitions can be omitted. All essential equations, transformations and calculations that are required for this 6-D fusion approach are derived. To highlight the meaning for practical implementations, numerous experiments with a six-joint Staeubli RX60 industrial manipulator are presented and the achieved results are discussed.

Indirect force control development procedure

“…18 There are also other ways to increase the robustness of the force control, e.g., based on the virtual environment concept. This method is qualitative and based on the previously assumed behavior of contact of the manipulator end-effector and the environment (Section 4).…”

“…For this purpose a precise multi-axis acceleration measurement in the manipulator end-effector is needed to filter out the majority of non-contact forces. 18 There are also other ways to increase the robustness of the force control, e.g., based on the virtual environment concept. 13…”

Robust disturbance estimation for human-robotic comanipulation

“…In parallel with force estimation strategies, based on DOB, another approach using sensor fusion has been developed to diminish the noise levels of the force sensors. In , force and acceleration sensors are combined, whereas in , data from force sensors and position encoders are fused. Sensor fusion provides better qualitative results than those obtained by employing more expensive force sensors.…”

Bilateral Teleoperation for Force Sensorless 1-Dof Robots

“…In parallel with force estimation strategies, based on disturbance observers, another approach using sensor fusion has been developed to diminish the noise levels of the force sensors. In (Kröger et al, 2007), force and acceleration sensors are used, while in (Garcia et al, 2008), data from force sensors and position encoders are fused. Sensor fusion provides better qualitative results than obtained by employing more expensive force sensors.…”