This paper introduces an edge-controlled autonomous robot with a gyro-stabilized active suspension system in form of a hybrid quadrupedal wheel drive mechanism, capable of detecting free pathways with an angular resolution of 1 degree and steering the robot in that direction. This features the computer-aided prototyping of the robot as a complete multisensory mechatronic system. Also, several algorithmic models were used in developing the robot’s software, which includes suspension control and pathfinding algorithms.
Route planning also known as pathfinding is one of the key elements in logistics, mobile robotics and other applications, where engineers face many conflicting objectives. However, most of the current route planning algorithms consider only up to three objectives. In this paper, we propose a scalable many-objective benchmark problem covering most of the important features for routing applications based on real-world data. We define five objective functions representing distance, traveling time, delays caused by accidents, and two route specific features such as curvature and elevation.