Affiliation:
1. Pondicherry University, India
Abstract
Robotics has become a rapidly emerging branch of science, addressing the needs of humankind by way of advanced technique, like artificial intelligence (AI). This chapter gives detailed explanation about the background knowledge required in implementing the software robots. This chapter has an in-depth explanation about different types of software robots with respect to different applications. This chapter would also highlight some of the important contributions made in this field. Path planning algorithms are required for performing robot navigation efficiently. This chapter discusses several robot path planning algorithms which help in utilizing the domain knowledge, avoiding the possible obstacles, and successfully accomplishing the tasks in lesser computational time. This chapter would also provide a case study on robot navigation data and explain the significant of machine learning algorithms in decision making. This chapter would also discuss some of the potential simulators used in implementing software robots.
Reference47 articles.
1. Reinforcement learning-based mobile robot navigation
2. Robotic motion control using machine learning techniques
3. Bley, A., & Martin, C. (2010). SCITOS G5 –A mobile platform for research and industrial applications. Retrieved from http://download.ros.org/data/Events/CoTeSys-ROS-School/metralabs.pdf
4. Brahmi, H., Ammar, B., & Alimi, A. M. (2013). Intelligent path planning algorithm for autonomous robot based on recurrent neural networks. Advanced Logistics and Transport (ICALT), 2013 International Conference on, 199–204.
5. A fast two-stage ACO algorithm for robotic path planning