Research On Indoor Laser Navigation System Of Mobile Service Robot

With the rapid development of robotics,intelligent mobile service robots increasingly appear in people’s daily life.As one of the important manifestations of intelligent mobile service robots,indoor autonomous navigation has become the key research direction.Usually,the indoor environment is complex,and thus it is often necessary to solve many problems for autonomous navigation.Therefore,the study of autonomous navigation system for mobile service robots in complex indoor environment is of great theoretical significance and practical value.The main work of this paper is as follows:Firstly,the current research status of mobile service robots,navigation technology and common sensors are outlined,and ROS(Robot Operating System)is selected as the software platform of the navigation system;besides,the laser scanner is used as the environmental information acquisition device.And the system design of indoor laser navigation of mobile service robot based on ROS is completed.Secondly,for the problem of RBPF-SLAM with low accuracy and poor robust estimation in the environment with noise interference,a SLAM algorithm based on RaoBlackwellized H∞ filtering is proposed.In the new algorithm,Iterated unscented H∞ filter is introduced to accurately calculate the importance density function,which is used to estimate the system state mean and covariance.Without deducing the Jacobian matrix,the accumulation of linearization errors is avoided.Moreover,with the iterative updating method,the system state mean and covariance is constantly corrected by using observation information,and the estimation error is further reduced.Simulation results show that the improved algorithm has high robustness,and it can build the environment map effectively and preciselyThirdly,with the study of Artificial Fish Swarm Algorithm(AFSA),an improved Artificial Fish Swarm Algorithm(IAFSA)based on adaptive optimization strategy is proposed.In this new algorithm,the Gaussian distribution function is introduced to dynamically adjust the control parameters,such as Visual and Step,and get the balance of the global optimization ability and the local optimization ability.To improve the search accuracy of the algorithm,the reverse learning strategy is introduced to construct the reverse learning fish swarm.Also,inspired by PSO algorithm,the operator based on PSO iterative weight is proposed to enhance the local search ability.Simulation results show that the improved AFSA algorithm has the great global optimization ability;the convergence speed is fast and precision is high,and the algorithm can get the optimal path.Finally,the ROS based indoor laser navigation system is constructed on the ROS2-bot mobile robot.Experimental of autonomous navigation are carried out in the artificial environment and the indoor environment of the building,respectively.Experiments results show that the indoor laser navigation system based on ROS has high adaptability and efficiency and it is very reliable.The proposed navigation system has high reliability.