Analysis andreview of robot path planning algorithms
With the rapid development of automation and artificial intelligence,mobile robots have been widely penetrated into all walks of life,and path planning technology is the key to ensuring their autonomy and efficiency.This paper deeply analyzes several mainstream path planning algorithms,including graph search,random sampling,intelligent bionics,and deep reinforcement learning,and reveals the advantages and challenges of each algorithm in practical applications.This paper further classifies the path planning research according to the application scenarios and specifically analyzes the path planning methods and development trends of land robots,unmanned aerial vehicles,and underwater robots in their respective fields.In addition,this paper also looks forward to the possible future development directions of path planning techniques.Through this overview,this paper aims to provide valuable information and research ideas for researchers in this field.
mobile robotpath planning algorithmalgorithm classificationbionic algorithmdeep reinforcement learning
万方数据
维普
