Providing mobile robots with autonomous capabilities is advantageous. It allows one to
dispense with the intervention of human operators, which may prove beneficial in economic …

Humanoid robots, unmanned rovers, entertainment pets, drones, and so on are great
examples of mobile robots. They can be distinguished from other robots by their ability to …

The implementation of Industry 5.0 necessitates a decrease in the energy consumption of
industrial robots. This research investigates energy optimization for optimal motion planning …

The Q-Learning algorithm is a reinforcement learning technique widely used in various
fields such as path planning, intelligent transportation, penetration testing, among others. It …

With the development of technology, mobile robots are becoming more and more common
in industrial production and daily life. Various rules are set to ensure that mobile robots can …

In this paper, a new method is proposed for the path planning of multi-robots in unknown
environments. The method is inspired by multi-objective particle swarm optimization …

Ant colony optimization (ACO) technique is proposed to solve the mobile robot path
planning (MRPP) problem. In order to demonstrate the effectiveness of ACO in solving the …

Ant colony optimization (ACO) is a meta-heuristic that is inspired by real ants that are
capable of exploring shortest paths, which inspires researchers to apply it for solving …

Path planning problem, is a challenging topic in robotics. Indeed, a significant amount of
research has been devoted to this problem in recent years. The ant colony optimization …

Aiming at the disadvantages of the basic ant colony algorithm, this paper proposes an
improved ant colony algorithm for robot global path planning. First, adjust the pheromone …