TY - GEN
T1 - Safe Navigation in Human Occupied Environments Using Sampling and Control Barrier Functions
AU - Majd, Keyvan
AU - Yaghoubi, Shakiba
AU - Yamaguchi, Tomoya
AU - Hoxha, Bardh
AU - Prokhorov, Danil
AU - Fainekos, Georgios
N1 - Funding Information:
1K. Majd and G. Fainekos ({majd,fainekos}@asu.edu) are with CIDSE, Arizona State University, Tempe, AZ, USA. This research was partially funded by NSF OIA 1936997 2S. Yaghoubi, T. Yamaguchi, D. Prokhorov, and B. Hoxha (<first name.last name>@toyota.com) are with the Toyota Research Institute of North America, Ann Arbor, MI, USA.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Sampling-based methods such as Rapidly-exploring Random Trees (RRTs) have been widely used for generating motion paths for autonomous mobile systems. In this work, we extend time-based RRTs with Control Barrier Functions (CBFs) to generate, safe motion plans in dynamic environments with many pedestrians. Our framework is based upon a human motion prediction model which is well suited for indoor narrow environments. We demonstrate our approach on a high-fidelity model of the Toyota Human Support Robot navigating in narrow corridors. We show in simulation results that our proposed online method can navigate safely in the presence of moving agents with unknown dynamics.
AB - Sampling-based methods such as Rapidly-exploring Random Trees (RRTs) have been widely used for generating motion paths for autonomous mobile systems. In this work, we extend time-based RRTs with Control Barrier Functions (CBFs) to generate, safe motion plans in dynamic environments with many pedestrians. Our framework is based upon a human motion prediction model which is well suited for indoor narrow environments. We demonstrate our approach on a high-fidelity model of the Toyota Human Support Robot navigating in narrow corridors. We show in simulation results that our proposed online method can navigate safely in the presence of moving agents with unknown dynamics.
UR - http://www.scopus.com/inward/record.url?scp=85116375408&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85116375408&partnerID=8YFLogxK
U2 - 10.1109/IROS51168.2021.9636406
DO - 10.1109/IROS51168.2021.9636406
M3 - Conference contribution
AN - SCOPUS:85116375408
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 5794
EP - 5800
BT - IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
Y2 - 27 September 2021 through 1 October 2021
ER -