Navigation of Autonomous Light Vehicles Using an Optimal Trajectory Planning Algorithm

Autonomous navigation is a complex problem that involves different tasks, such as location of the mobile robot in scenario, robotic mapping, generating trajectory, navigating from initial point to target point, detecting objects it may encounter its path, etc. This paper presents new optimal trajectory planning algorithm allows assessment energy efficiency autonomous light vehicles. To best our knowledge, this first time literature carried out by minimizing travel while considering vehicle’s dynamic behavior, limitations, and with capability avoiding obstacles constraining consumption. enables automotive industry design environmentally sustainable strategies towards compliance governmental greenhouse gas (GHG) emission regulations for climate change mitigation adaptation policies. The reduction consumption also companies stay competitive marketplace. vehicle control efficiently implemented through middleware component-based software development (CBSD) based on Robot Operating System (ROS) package. It boosts reuse components systems other existing systems. Therefore, avoidance architectures integrate hardware components. global maps are created scanning environment FARO 3D 2D SICK laser sensors. proposed low computational cost has been module distributed architecture. integrated into ROS package achieve real vehicle. methodology successfully validated indoor experiments using under scenarios entailing several obstacle locations parameters.