Abstract-Existing path planning algorithms are capable of finding physically feasible, shortest, and energy-efficient paths for mobile robots navigating on uneven terrains. However, shortest paths on uneven terrains are often energy inefficient while energy-optimal paths usually take long time to be traversed. Therefore, due to time and energy constraints imposed on mobile robots, these shortest and energy-optimal paths might not be applicable. We propose a multiobjective path planner that can find pareto-optimal solutions in terms of path length and energy consumption. It is based on NAMOA* search algorithm that utilizes a proposed monotone heuristic cost function. The simulation results show that nondominated path options found by the proposed path planner can be very useful in many realworld applications.
The work in REF proposes a multi-objective path finder that can discover Pareto-optimal solutions concerning energy consumption and length of the path.
Multiobjective path planning on uneven terrains based on NAMOA*
2016 IEEE International Symposium on Circuits and Systems (ISCAS)
2016 IEEE International Symposium on Circuits and Systems (ISCAS)
Computer Science