Dynamical attitude configuration with wearable wireless body sensor networks through beetle antennae search strategy

•Random search method for the manipulator obtains an optimal attitude configuration.•Multiple information fusion adjusts search directions in process of path planning.•Self-attenuation of the alternative step reduces the consumption of calculation.•Local cascade search loop improves initial search step of intelligence optimization. Wearable wireless body sensor networks (WWBSN) are helpful to the dynamical attitude configuration of human-like robots. And then, we employ the Beetle Antennae Search (BAS) algorithm for a field robot to obtain an optimal solution to both path planning and attitude configuration by using the measurements of WWBSN. In terms of obstacle avoidance further more, the proposed Beetle Antennae Search for Attitude Optimization (BASAO) of manipulator develops two important mechanisms, including both experience-oriented part and inner loop step self-attenuate part, to enhance the efficiency and accuracy. earch efficiency is improved by fusing the target information via guidance strategy, and the optimization of each iteration is coordinated by local self-decaying step size. For manipulators mounted with WWBSN, the proposed method is implemented in three-dimensional attitude planning simulations, some of which consider a challenging obstacle situation. Simulation results show that the proposed BASAO algorithm is effective in the attitude planning with WWBSN, compared with the traditional Rapidly-exploring Random Tree (RRT) algorithm.