FTA-Sensor: Combination of Force/Torque and Acceleration - Robotized Transcranial Magnetic Stimulation - page 98

Chapter 6
FTA-Sensor: Combination
of Force/Torque and Acceleration
The implemented Force-Torque (FT)-control so far greatly enhances the system's
usability (compare to Sect. 5.3.2 ). However, general safety of the robotized TMS
system cannot be achieved with the presented implementation. As all necessary
computations are performed in software, safety can only be achieved on a software
layer (cf. Sect. 5.2 ). This implementation does not provide additional safety to the
hardware layer. Due to the setup, an additional latency is unavoidable. On one
hand this results in slow robot movements for the hand-assisted positioning. On the
other hand, a robot stop in case of an error or collision cannot be performed
instantaneously. The latency is roughly 200 ms (see Sect. 5.3.3 ).
For accurate force and torque detection during operation, the tool's weight
related forces and torques must be subtracted. As this impact changes depending
on the spatial orientation due to gravity, the spatial orientation of the sensor must
be known. Commonly, this is done by using the current robot end effector's pose
(cf. Sect. 5.1.2 ) . Beside additional latencies, the communication with the robot
controller is mostly done in software and the computation is not independent of the
robot. In case of a robot (encoder) fault, this might not be detected with the FT
sensor.
Therefore, we introduce an independent safety system that is easy to integrate
in the existing systems and adds to them an additional safety layer. It is based on
an FT sensor which is combined with an Inertia Measurement Unit (IMU), named
Force-Torque Acceleration (FTA) sensor. An embedded system runs a real-time
monitoring cycle and instantaneously (within 1 ms) triggers the robot's Emer-
gency stop (e-stop) in case of an error or detected collision. As another key feature,
the embedded system provides gravity compensation independently from robot
input in real-time using the acceleration recordings.
In this chapter, we present the idea of combining acceleration measurements
with an FT-sensor for independence from robot input. We systematically present
the implementation and setup of the FTA sensor on the embedded system.
Furthermore, we describe the real-time monitoring cycle in detail and highlight its
Parts of this chapter have been already published in [ 1 , 2 ].