TY - JOUR
T1 - Dynamic contact force/torque observer
T2 - Sensor fusion for improved interaction control
AU - Bätz, Georg
AU - Weber, Bernhard
AU - Scheint, Michael
AU - Wollherr, Dirk
AU - Buss, Martin
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The author gratefully acknowledges doctoral funding received from the joint Economic and Social Research Council and Natural Environment Research Council interdisciplinary studentships, grant number ES/I902961/1.
PY - 2013/4
Y1 - 2013/4
N2 - The potential areas of application for robots have gradually extended beyond the classical industrial settings in large-scale enterprizes: nowadays, the integration of robots into daily life has become a central development in robotics. Here, one major challenge is the physical interaction with unknown and/or changing environments. Such an interaction requires knowledge of the exchanged contact forces and torques. To this end, robotic systems are typically equipped with force/torque sensors at the wrist. By using force control schemes that rely on measurements from these sensors, conventional manipulation tasks are successfully executed. In particular, for dynamic manipulation tasks, however, the problem arises that the inertial forces/torques of the end effector have a non-negligible effect on the measurements of the wrist sensor. This degrades the performance of the interaction control and constitutes a safety risk since the actual interaction forces/torques deviate from the desired values. As a solution to this problem, the paper discusses four contact force/torque observer designs: two approaches are based on the extended Kalman filter (EKF) and two approaches are based on the unscented Kalman filter (UKF). For both types, EKF and UKF, two different measurement vectors are considered: the first one only uses pose and force/torque measurements, whereas the second one also uses acceleration measurements to determine the contact forces and torques. The four observer designs are evaluated in simulation and experiment for six-degree-of-freedom (DOF) tasks.
AB - The potential areas of application for robots have gradually extended beyond the classical industrial settings in large-scale enterprizes: nowadays, the integration of robots into daily life has become a central development in robotics. Here, one major challenge is the physical interaction with unknown and/or changing environments. Such an interaction requires knowledge of the exchanged contact forces and torques. To this end, robotic systems are typically equipped with force/torque sensors at the wrist. By using force control schemes that rely on measurements from these sensors, conventional manipulation tasks are successfully executed. In particular, for dynamic manipulation tasks, however, the problem arises that the inertial forces/torques of the end effector have a non-negligible effect on the measurements of the wrist sensor. This degrades the performance of the interaction control and constitutes a safety risk since the actual interaction forces/torques deviate from the desired values. As a solution to this problem, the paper discusses four contact force/torque observer designs: two approaches are based on the extended Kalman filter (EKF) and two approaches are based on the unscented Kalman filter (UKF). For both types, EKF and UKF, two different measurement vectors are considered: the first one only uses pose and force/torque measurements, whereas the second one also uses acceleration measurements to determine the contact forces and torques. The four observer designs are evaluated in simulation and experiment for six-degree-of-freedom (DOF) tasks.
KW - interaction control
KW - observer design
KW - sensor fusion
UR - http://www.scopus.com/inward/record.url?scp=84876583549&partnerID=8YFLogxK
U2 - 10.1177/0278364913482015
DO - 10.1177/0278364913482015
M3 - Article
AN - SCOPUS:84876583549
SN - 0278-3649
VL - 32
SP - 446
EP - 457
JO - International Journal of Robotics Research
JF - International Journal of Robotics Research
IS - 4
ER -