TY - JOUR
T1 - Robust Sequential Trajectory Planning under Disturbances and Adversarial Intruder
AU - Chen, Mo
AU - Bansal, Somil
AU - Fisac, Jaime F.
AU - Tomlin, Claire J.
N1 - Funding Information:
Manuscript received November 25, 2016; revised November 5, 2017; accepted March 17, 2018. Date of publication May 8, 2018; date of current version June 11, 2019. Manuscript received in final form April 10, 2018. This work was supported in part by NSF through the CPS Frontiers VehiCal Project under Grant 1545126, in part by the UC-Philippine-California Advanced Research Institute under Project IIID-2016-005, and in part by ONR MURI Embedded Humans under Grant N00014-16-1-2206. The work of M. Chen was supported the NSERC Program. The work of J. F. Fisac was supported by the “la Caixa” Foundation. Recommended by Associate Editor M. Zefran. Corresponding author: Mo Chen.) M. Chen is with the Department of Aeronautics and Astronautics, Stanford University, Stanford, CA 94305 USA (e-mail: mochen72@stanford.edu).
Funding Information:
This work was supported in part by NSF through the CPS Frontiers VehiCal Project under Grant 1545126, in part by the UC-Philippine-California Advanced Research Institute under Project IIID-2016-005, and in part by ONR MURI Embedded Humans under Grant N00014-16-1-2206. The work of M. Chen was supported the NSERC Program. The work of J. F. Fisac was supported by the "la Caixa" Foundation. Recommended by Associate Editor M. Zefran.
Publisher Copyright:
© 1993-2012 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - Provably safe and scalable multivehicle trajectory planning is an important and urgent problem. Although this problem has been studied in the past, there has not been a method that guarantees both goal satisfaction and safety for vehicles with general nonlinear dynamics, while taking into account disturbances and potential adversarial agents, to the best of our knowledge. Hamilton-Jacobi (HJ) reachability is the ideal tool for guaranteeing goal satisfaction and safety under such scenarios, which has been successfully applied to many small-scale problems; however, its direct application in most cases becomes intractable when there are more than two vehicles due to the exponentially scaling computational complexity with respect to system dimension. In this paper, we take advantage of the guarantees provided by HJ reachability and eliminate the computation burden by assigning a strict priority ordering to vehicles under consideration. Under this sequential trajectory planning (STP) scheme, vehicles reserve 'space-time' portions in the airspace. The space-time portions guarantee dynamic feasibility, collision avoidance, and optimality of trajectories given the priority ordering. With a computation complexity that scales quadratically when accounting for both disturbances and an intruder, and linearly when accounting for only disturbances, the STP can tractably solve the multivehicle trajectory planning problem for vehicles with general nonlinear dynamics in a practical setting. We demonstrate our theory in representative simulations.
AB - Provably safe and scalable multivehicle trajectory planning is an important and urgent problem. Although this problem has been studied in the past, there has not been a method that guarantees both goal satisfaction and safety for vehicles with general nonlinear dynamics, while taking into account disturbances and potential adversarial agents, to the best of our knowledge. Hamilton-Jacobi (HJ) reachability is the ideal tool for guaranteeing goal satisfaction and safety under such scenarios, which has been successfully applied to many small-scale problems; however, its direct application in most cases becomes intractable when there are more than two vehicles due to the exponentially scaling computational complexity with respect to system dimension. In this paper, we take advantage of the guarantees provided by HJ reachability and eliminate the computation burden by assigning a strict priority ordering to vehicles under consideration. Under this sequential trajectory planning (STP) scheme, vehicles reserve 'space-time' portions in the airspace. The space-time portions guarantee dynamic feasibility, collision avoidance, and optimality of trajectories given the priority ordering. With a computation complexity that scales quadratically when accounting for both disturbances and an intruder, and linearly when accounting for only disturbances, the STP can tractably solve the multivehicle trajectory planning problem for vehicles with general nonlinear dynamics in a practical setting. We demonstrate our theory in representative simulations.
KW - Collision avoidance
KW - multi-robot systems
KW - optimal control
KW - safety-critical systems
KW - trajectory planning
KW - unmanned aerial vehicles
KW - unmanned airspace traffic management
UR - http://www.scopus.com/inward/record.url?scp=85046749410&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046749410&partnerID=8YFLogxK
U2 - 10.1109/TCST.2018.2828380
DO - 10.1109/TCST.2018.2828380
M3 - Article
AN - SCOPUS:85046749410
SN - 1063-6536
VL - 27
SP - 1566
EP - 1582
JO - IEEE Transactions on Control Systems Technology
JF - IEEE Transactions on Control Systems Technology
IS - 4
M1 - 8356101
ER -