Optimally Trading Energy for Information through Speed Trajectory Optimization of Sustainably Powered Mobile Robots
The research optimizes how a mobile robot should spend its limited battery energy while moving along a fixed path to maximize the quality of information collected over time. It models this as a control problem where energy cost is super-linear and information gain decays. The findings show that the robot should slow down in areas where sensing is most important and speed up in less important areas to achieve better overall data clarity.