US 12,253,839 B2
Method and device for determining an optimized control strategy of a mobile agent in a dynamic objects environment
Niels Van Duijkeren, Kornwestheim (DE); Luigi Palmieri, Leonberg (DE); and Ralph Lange, Rutesheim (DE)
Assigned to ROBERT BOSCH GMBH, Stuttgart (DE)
Filed by Robert Bosch GmbH, Stuttgart (DE)
Filed on Jun. 10, 2021, as Appl. No. 17/344,257.
Claims priority of application No. 20190608 (EP), filed on Aug. 12, 2020.
Prior Publication US 2022/0050429 A1, Feb. 17, 2022
Int. Cl. G05B 13/04 (2006.01); B60W 30/095 (2012.01); G05B 17/02 (2006.01); G05D 1/00 (2006.01); G05D 1/02 (2020.01)
CPC G05B 13/048 (2013.01) [B60W 30/0953 (2013.01); G05B 13/041 (2013.01); G05B 17/02 (2013.01); G05D 1/0217 (2013.01); G05D 1/0219 (2013.01); B60W 2400/00 (2013.01)] 8 Claims
OG exemplary drawing
 
1. A computer-implemented method for determining an appropriate control strategy for a mobile agent for an environment with a plurality of dynamic objects, comprising the following steps:
providing a number of different scenarios, wherein, to each of the scenarios a plurality of dynamic objects is associated, wherein for each of the scenarios, each of the dynamic objects of the plurality of dynamic objects is associated with a start, a goal, and a behavior specification;
providing a number of control strategy candidates for the mobile agent;
benchmarking each of the control strategy candidates in any of the scenarios; and
selecting a control strategy for the mobile agent depending on a result of the benchmarking of the control strategy candidates,
wherein the benchmarking of each respective control strategy candidate of the control strategy candidates in every scenario is performed depending on results of optimization problems to reflect behaviors of each dynamic object of the plurality of dynamic objects the mobile agent may face during application of the respective control strategy candidate in the benchmarking, wherein the behaviors of each dynamic object of the plurality of dynamic objects is defined by an optimal control problem which results in a tuning of the behaviors of each dynamic object of the plurality of dynamic objects, wherein the optimization is performed simultaneously with the benchmarking for each dynamic object of the plurality of dynamic objects,
wherein each of the control strategy candidates applies a cost function or is rule-based to optimize a motion trajectory for the mobile agent in the environment with the plurality of dynamic objects, and
controlling the mobile agent based on the selected control strategy.