TY - GEN
T1 - Reachset Conformance of Forward Dynamic Models for the Formal Analysis of Robots
AU - Liu, Stefan B.
AU - Althoff, Matthias
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/27
Y1 - 2018/12/27
N2 - Model-based design of robotic systems has many advantages, among them faster development cycles and reduced costs due to early detections of design flaws. Approximate models are sufficient for many classical robotic applications; however, they no longer suffice for safety-critical applications. For instance, a dangerous situation which has not been detected by model-based testing might occur in a human-robot coexistence scenario since models do not exactly replicate behaviors of real systems-this problem arises no matter how accurate a model is, since even disturbances and sensor noise can cause a mismatch. We address this issue by adding nondeterminism to robotic models and by computing the whole set of possible behaviors using reachability analysis. By using reachset conformance, we automatically adjust the required non-determinism so that all recorded behaviors are captured. For the first time this approach is demonstrated for a real robot.
AB - Model-based design of robotic systems has many advantages, among them faster development cycles and reduced costs due to early detections of design flaws. Approximate models are sufficient for many classical robotic applications; however, they no longer suffice for safety-critical applications. For instance, a dangerous situation which has not been detected by model-based testing might occur in a human-robot coexistence scenario since models do not exactly replicate behaviors of real systems-this problem arises no matter how accurate a model is, since even disturbances and sensor noise can cause a mismatch. We address this issue by adding nondeterminism to robotic models and by computing the whole set of possible behaviors using reachability analysis. By using reachset conformance, we automatically adjust the required non-determinism so that all recorded behaviors are captured. For the first time this approach is demonstrated for a real robot.
UR - http://www.scopus.com/inward/record.url?scp=85062986086&partnerID=8YFLogxK
U2 - 10.1109/IROS.2018.8593975
DO - 10.1109/IROS.2018.8593975
M3 - Conference contribution
AN - SCOPUS:85062986086
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 370
EP - 376
BT - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
Y2 - 1 October 2018 through 5 October 2018
ER -