Prediction and Obstacle Avoidance Detection Algorithm Based on Driverless
This paper proposes the optimal path avoidance algorithm based on the cat-cluster algorithm for the optimal trajec-tory of unmarked target position in a chaotic environment.First,a systematic error model for the controller design that is suitable for the simultaneous search of the trajectory and the target position will be derived,and the original control problem is transformed into the problem of the automatic update rate of the uncertain parameters and the minimization of the maximum path distance.Secondly,by estimating the automatic update rate online,the trajectory generated by the proposed algorithm is guaranteed to be the minimum length and collision-free,and the allocation strategy minimizes the maximum travel distance.Finally,experimental simulations show that the proposed algorithm can be used accurately for path prediction and obstacle avoidance detection,and suppress the in-fluence of system parameter uncertainty on the control system.
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