Tracking Design of an Omni-Direction Autonomous Ground Vehicle by Hierarchical Enhancement Using Fuzzy Second-Order Variable Structure Control

Abstract

Owing to the hierarchical architecture of the derived model of the omni-direction autonomous ground vehicle (OD-AGV), the virtual desired trajectory (VDT) is first designed by the first switching surface, which is set as the linear dynamic pose error of the OD-AGV. In sequence, the trajectory tracking control (TTC) is designed by the second switching surface, which is the linear dynamic tracking error of the VDT. To deal with nonlinear time-varying uncertainties including system disturbance and different ground conditions, enhanced fuzzy second-order variable structure control (EF2VSC) is designed into both VDT and TTC. Finally, the experiments for tracking the circular trajectories with different curvatures, traveling velocities, and poses of the OD-AGV are presented to validate the effectiveness and robustness of the proposed hierarchical enhancement using fuzzy second-order variable structure control (HEF2VSC).

Interactions Between Specific Human and Omnidirectional Mobile Robot Using Deep Learning Approach: SSD-FN-KCF

“…If the SH is identified, the SH will be tracked by the KCF [24]- [28] to avoid the repeated calculation of the FaceNet. Afterward, the corresponding interactions between the SH and the ODMR (e.g., human following control) are implemented by the image-based adaptive finite-time hierarchical constraint control (IB-AFTHCC) [17], [18]. If the face of detected human is difficult to recognize, the ODMR will be commanded to a suitable pose to execute the FaceNet algorithm.…”

“…Based on the information of image processing, the required pose tracking for searching or tracking (specific) human is achieved by the ODMR with AFTHCC [17], [18]. At first, the kinematic relation of the ODMR is depicted in Fig.…”

“…In this paper, the SSD is first employed to detect the human(s), which is (are) not necessarily static. If human is not detected, the ODMR will execute the search of human by the image-based adaptive finitetime hierarchical constraint control (IB-AFTHCC) [17], [18]. After the detection of human, the ODMR approaches the detected human with an appropriate distance (e.g., 2.5∼3m).…”

Software/Hardware-Based Hierarchical Finite-Time Sliding-Mode Control With Input Saturation for an Omnidirectional Autonomous Mobile Robot

“…The appropriate tuning of these switching gains can maintain the faster trajectory tracking performance with the reduced chattering feature. Based on the above analyses, the consideration of the motor dynamics possesses the advantages for the simultaneous translation and rotation of trajectory tracking control, the initial misalignment of OAMR (cf., [17], [18], [29], and the contribution (i)). Based on these requirements, the proposed hierarchical control is designed by two sliding surfaces with the linear dynamics and fractional order for both FTVDT and FTSMSC with time-varying switching gains (cf.…”

“…Hence, trajectory planning, obstacle avoidance, trajectory tracking, and navigation of mobile robots have become popular topics in the robotic field, e.g., [1]- [5]. There are many types of autonomous mobile robot, e.g., differential, car-like, omnidirectional, multi-segment continuum robot, and tractor-andtrailer types [6]- [18]. Each type has different kinematics,…”