Improved Techniques for Autonomous Robots Development using Sensors Fusion in Indoor Environment
In the past two decades, the world of robotics has seen tremendous progress, which has spread them all over the world. Whether in the military, industrial or civil fields, robots are making human life easier in daily tasks. For example, they are often used near the people for cooperation in complex environment (such as narrow spaces, rugged ground), with some static obstacles. These obstacles can be dynamic sometimes, this increase the complexity of the robots’ localization and navigation tasks. In this context, it is useful to build much more performant robots’ navigation algorithms. As the mobile robots are used more than more in the very near proximity to people. So this thesis proposes some new algorithms and techniques to improve some existing techniques and methods used in the development of the robots in order to avoid the accidents, financial loses and bring more security in the field of the robotic. To reach these goals, the following four major innovative contributions have been achieved along this research thesis:
(1) At first, a new navigation algorithm named “Novel Infrared Navigational Algorithm” (NIRNA) has been created based on some cooperating infrared (IR) sensors. This algorithm is then integrated into an odometric system to build a navigation subsystem (Odom-NIRNA). Next, an Inertial Navigation System (INS) is used as the second navigation subsystem. These two subsystems are used to build a hybrid navigation system using Unscented Kalman Filter. The whole system aims to improve the estimated robot’s navigation data. Two simulation tests are conducted and the results showed that the built system using NIRNA outperforms that of some existent navigation algorithms such as HCTNav.
(2) Hierarchical model of novel IRNA Hybridization (HIRNAH) is the second hybridization algorithm built in this research thesis. It is a three level tightly hybridization system to give an accurate navigational data. Both simulations and real-life experiments are conducted to evaluate the built system’s performance. The simulation results showed that HIRNAH is feasible and reliable. Thus its prototype has been built and mounted on a four wheeled mobile robot (4-WMR). Experimental results confirm that HIRNAH presents higher accuracy estimation and lower mean-square error (MSE) for robot state than for instance, EKF and UKF.
(3) Third contribution describes the design and implementation of a Power Management System (PMS) for the autonomous robots. This new PMS controls the battery recharging process in both the robot and its charger, and then allowing a redundant verification (repetitive) of the connection status between the robot and its charger. Thus a prototype IC board has been built and mounted on a 4-WMR. In this designed PMS, the risk of electrical damage is avoided when connecting the robot to the charger.
(4) The fourth contribution of the thesis is the design and implementation of a new robot’s docking strategy with battery auto-recharging possibility. This docking strategy is based on Infrared (IR) communication. It is using six IR sensors to help the robot to dock to the charger. So that to determine the shortest arrival time (SAT) of the robot to the charger. Many experiments are conducted with different scenarios characterized by different positions of the IRRs on the robot. The experimental results on the collected data allowed to identify the best positions and orientation angle on the robot where to position these IRRs.
Doumbia, M.; Cheng, X. "State Estimation and Localization Based on Sensor Fusion for Autonomous Robots in Indoor Environment," Computers 2020, 9, 84. (SCI, Tutor first author).
Doumbia, M.; Cheng, X. and Xiaohan TU, "A Tightly Hybridization based on Novel Infrared NavigationalAlgorithm for Autonomous Robots in Indoor Environment", Journal of Robotic. (Under review). (SCI, Tutor first author).
M. Doumbia, X. Cheng and L. Chen, "A Novel Infrared Navigational Algorithm for Autonomous Robots," 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS), Dalian, China, 2020, pp. 86-92, (EI, Tutor first author)
M. Doumbia, X. Cheng and H. Chen, "A novel Power Management System for Autonomous Robots," Future Technologies Conference (FTC) 2019, San Francisco, United States, 2019, AISC 1070, pp. 293-305, 2020. (EI, Tutor first author)
M. Doumbia, X. Cheng and V. Havyarimana, "An Auto-Recharging System Design and Implementation Based on Infrared Signal for Autonomous Robots," 2019 5th International Conference on Control, Automation and Robotics (ICCAR), Beijing, China, 2019, pp. 894-900. (EI, Tutor first author)
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