A digital twin-based optimal trajectory generation method and system

Abstract

The invention discloses a digital twin-based optimal trajectory generation method and system. The system includes: a data transmission interface, a data interaction interface, a trajectory planning module, and a digital mapping module; the trajectory planning module includes: a planner component and a robot physics module. Model assembly; The digital mapping module includes: an environment model and an agent model; the main function of the trajectory planning module is to generate a corresponding optimal control problem according to the planning task, and solve the problem through a numerical algorithm; one of the main functions of the digital mapping module It is to quickly generate the control quantity trajectory and state quantity trajectory without collision and satisfy the robot dynamics constraints; the second function is to quickly realize the deviation evaluation and collision detection of the target trajectory. The beneficial effects are: it can take into account energy consumption while improving work precision and efficiency; it can be applied to work scenes with higher motion speed and stricter control precision requirements; optimization.

Description

technical field [0001] The present invention relates to the fields of optimal control and digital twins, in particular to a digital twin-based optimal trajectory generation method and system. Background technique [0002] Motion planning can be divided into path planning and trajectory planning, where path planning refers to the calculation of the entire collision-free state transition process from the initial state to the target state; trajectory planning is based on path planning for each intermediate state Added time-of-arrival information, which calculates the time history of all state changes. The result of path planning needs to be realized by the path tracking method of the controller, and trajectory planning can usually directly or indirectly calculate the control law. [0003] Currently popular path planning methods include heuristic search algorithms represented by A*, D* and their variants. This algorithm is a grid-based search method and is suitable for low-dime...

AI Technical Summary

Problems solved by technology

The traditional motion planning method executes the path planning program and the collision detection program in sequence; or introduces the "pruning" operation to execute the two programs alternately, which belongs to an "online" collision detection method, resulting in a certain time overhead

The optimal control method needs to predict the position or time when the collision may occur, and then avoid the collision point by adding a penalty item to the objective function or in a staged manner; however, for different planning tasks, it is unrealistic to predict the collision, that is, It cannot be explicitly integrated into the problem description of optimal control, and the distance between the robot and obstacles can only be guaranteed in an additional way; therefore, the current trajectory planning based on the optimal control method is difficult to apply to the work scene with dense obstacles

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