Aiming at the problem that the 6-DOF manipulator can quickly avoid obstacles in high-dimensional space, the method of path planning based on the improved rapid expansion random tree (RRT) algorithm is proposed. The improved RRT algorithm combines the advantages of the target bias strategy and proposes a method for setting the intermediate bias point. In random sampling, the sampling point is biased to the intermediate bias point,with a certain probability to reduce the blindness of sampling, and use at the same time the path shortening method reduces path nodes and turning points, and optimizes the motion path of the robotic arm. By comparing the simulation results with the RRT and P-RRT algorithms, the effectiveness of the improved RRT algorithm in the calculation time and the number of path nodes is proved.

This paper deals with the problem of asynchronous event-triggered guaranteed cost control for two-dimensional Markov jump systems in Roesser model. The hidden Markov model is introduced to characterize the asynchronous phenomenon induced by imperfect mode detection, and a hidden Markov model-based event-triggered mechanism is employed in controller design to reduce the communication burden of the network. By using the quadratic Lyapunov function technique, some sufficient criteria are developed to ensure the asymptotic stability of the addressed system with a guaranteed cost value under three different boundary conditions. Finally, an optimization algorithm with linear matrix inequality constraints is formulated to design the optimal asynchronous event-triggered guaranteed cost control law, and a simulation example is considered to illustrate its validity.