×
The submission system is temporarily under maintenance. Please send your manuscripts to
Go to Editorial ManagerAutonomous mobile robots (AMRs) are becoming increasingly important in different domains such as healthcare, warehouse automation and household duties, but still encounter problems when it comes to moving around unfamiliar and dynamic environments. This study proposes an advanced robotic navigation system which combines the Soft Actor-Critic (SAC) approach and Vector Field Histogram (VFH) for path planning and avoidance obstacles in completely unknown environments. This system leverages the strengths of deep reinforcement learning and real-time obstacle detection to achieve robust and efficient navigation in certain scenarios. The SAC strategy optimizes robot navigation using policy networks and Q-networks, while the VFH method addresses obstacle avoidance by sensor data processing and dynamically adjusting the robot’s angular velocity to avoid collision. For testing and implementing this system, Gazebo simulation and Robot Operating System (ROS) are used. Experimental results demonstrated that the proposed method outperformed the standard technique and achieved a high success rate in path planning and obstacles avoidance.
The last few years Quadrotor became an important topic, many researches have implemented and tested concerning that topic. Quadrotor also called an unmanned Aerial Vehicle (UAV), it's highly used in many applications like security, civil applications, aid, rescue and a lot of other applications. It’s not a conventional helicopter because of small size, low cost and the ability of vertical and takeoff landing (VTOL). The models kept an eye on quadrotors were presented, the advancement of this new kind of air vehicle is hindered for a very long while because of different reasons, for example, mechanical multifaceted nature, enormous size and weight, and challenges in charge particularly. Just as of late a lot of interests and endeavors have been pulled in on it; a quadrotor has even become a progressively discretionary vehicle for useful application. Quadrotor can be used in variable, different , outdoor and indoor missions; these missions should be implemented with high value of accuracy and quality. In this work two scenarios suggested for different two missions. First mission the quadrotor will be used to reach different goals in the simulated city for different places during one flight using path following algorithm. The second mission will be an indoor arrival mission, during that mission quadrotor will avoid obstacles by using only Pure pursuit algorithm (PPA). To show the benefit of using the new strategy it will compare with a victor field histogram algorithm (VFH) which is used widely in robotics for avoiding obstacles, the comparison will be in terms of reaching time and distance of reaching the goal. The Gazebo Simulator (GS) is used to visualize the movement of the quadrotor. The gazebo has another preferred position it helps to show the motion development of the quadrotor without managing the mathematical model of the quadrotor. The Robotic Operating System (ROS) is used to transfer the data between the MATLAB Simulink program and the Gazebo Simulator. The diversion results show that, the proposed mission techniques win to drive the quarter on the perfect route similarly at the limit with regards to the quadrotor to go without hitting any obstacle in the perfect way.