An Integrated Beetle Antennae Search–Enabled Navigation Framework for Omnidirectional AGVMobile Robots in Unknown Environments

The Beetle Antennae Search algorithm is a relatively one of the recent optimization approach inspired by the foraging behavior of long-horn beetles, that copy how they use their antennae to explore the environment. This algorithm due to its simple structure and derivative-free nature, is well suited for robotic applications with limited computational resources. Despite many BAS-based navigation studies still handle path planning and control independently, or apply BAS only as an offline trajectory optimization tool. As a result, less attention has been given to implement it in the real-time navigation framework. On the other hand, Mobile robots, in an unseen environment cannot work these problems separately rather they must continuously detect obstacles, update their environment model, keep re-planning safe routes, adjust control gains, and follow a predetermined reference trajectory. An integrated BAS-enabled navigation combining Simultaneous Localization and Mapping framework for an omnidirectional mobile robot in CoppeliaSim is presented in this research. A LiDAR-based occupancy grid is updated continually during motion, and obstacle detection via SLAM is used to improve safety. A modified A* algorithm is used to create collision-free avoidance pathways, which are then smoothed. At the same time, a BAS-driven adaptive PID controller is used to adjust the gains by using trajectory deviation as a feedback signal. To enable precise path following, a nine-sensor infrared array is used for line tracking. The integrated system can follow smoothed avoidance paths, calculate safe bypasses, identify impediments, and return to the original path. In the experiments, the system was tested in two scenarios - no obstacles and with three levels of obstacles. The results indicated higher performance when SLAM and BAS used together than conventional PID based navigation while software simulation of SLAM often hurting the performance as well.