Abstract
Although the traditional amphibious robot has the ability of multi-space motion, it has the disadvantage of low power utilization and no operational capability. In order to make it competent in an extremely complex environment, we studied the structural design and control of amphibian robot with operational capability. First, in order to make the robot have the ability of flying in the sky, moving on land, and swimming in the water, a “bevel variant” mechanism for power switching is designed. Then, taking the uncertainty of the kinetic parameters and external influences into account, the kinetic and kinematic models of the system are established. Next, a sliding mode controller that outputs control force for the system and a quadratic calculation optimization algorithm for inverse kinematics solution are designed. Finally, the simulation platform for the system is built based on MATLAB. The simulation results show that when the system is in the land and air flight stages, the vehicle position and orientation tracking error are within ±0.05 m and ±2°, respectively. When the system is in the underwater stage, the end effector position and orientation tracking error are within ±0.15 m and ±3.0°, respectively.
Highlights
On June 23, 2018, 12 junior football players and a coach from Thailand entered a cave to explore in Chiang Rai
The simulation results show that the amphibious variant vehicle-manipulator system (AVVMS) has good trajectory tracking ability under the control of this scheme, and the end manipulator has higher positioning accuracy when performing tasks
In order to improve the accuracy of inverse kinematics solution, we proposed the quadratic computational optimization algorithm based on the selection advantage of the weighted pseudo-inverse method and the precision advantage of the fixed joint angle method
Summary
On June 23, 2018, 12 junior football players and a coach from Thailand entered a cave to explore in Chiang Rai. Chen et al simplified the design of the control system by simplifying the kinematics and dynamics equations of the vehicle-manipulator system, but the accuracy of the simulation results is reduced.[4] Mohan and Kim designed an adaptive coordinated controller based on Kalman filter, but the controller relies on the accuracy of the filter.[5] Antonelli et al used the sliding mode control as the dynamic controller to control the underwater vehicle-manipulator system, but ignored the non-matching of ocean currents and the coupling of motion.[6,7,8,9,10,11,12] Zhang et al used the weighted minimum norm method to avoid joints reaching the angular limit position and the interference between the vehicle and the manipulator, but the tracking error of the end effector increases with time.[13,14]. The simulation results show that the AVVMS has good trajectory tracking ability under the control of this scheme, and the end manipulator has higher positioning accuracy when performing tasks
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
