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Research Article

Hybrid robust disturbance rejection position-force control to adjust the motion of mobile manipulator in automatic aluminum foundry recycling industries

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Pages 1-19 | Received 22 Nov 2023, Accepted 09 Feb 2024, Published online: 19 Apr 2024

Figures & data

Figure 1. Motion example of the mobile manipulator showing the tasks that must be completed before grasping the object, during the contact, and after carrying it.

Render of the operative scenario for the mobile manipulator in different times of task development.
Figure 1. Motion example of the mobile manipulator showing the tasks that must be completed before grasping the object, during the contact, and after carrying it.

Figure 2. Scheme of the robot with all its frames.

Render of the mobile manipulator with all its joints reference frameworks.
Figure 2. Scheme of the robot with all its frames.

Figure 3. Operating diagram for the MR considering the definition of the hybrid system used in this study.

Figure 3. Operating diagram for the MR considering the definition of the hybrid system used in this study.

Figure 4. Employed algorithm flow.

Figure 4. Employed algorithm flow.

Table 1. Initial gain’s condition of the robotic device.

Figure 5. Trajectory tracking for each DoF of the Kuka robot.

Figure 5. Trajectory tracking for each DoF of the Kuka robot.

Figure 6. Temporal evolution of the error for each DoF of the Kuka robot.

Figure 6. Temporal evolution of the error for each DoF of the Kuka robot.

Table 2. Comparison of the mean square error values for the different control laws at each stage for the Kuka robot.

Table 3. Comparison of the error integral values for the different control laws at each stage for the Kuka robot.

Figure 7. Temporal evolution of the error for the PLMR.

Figure 7. Temporal evolution of the error for the PLMR.

Figure 9. Temporal evolution of the control for each DoF of the Kuka robot.

Figure 9. Temporal evolution of the control for each DoF of the Kuka robot.

Figure 8. Temporal evolution of the control for the PLMR.

Figure 8. Temporal evolution of the control for the PLMR.

Table 4. Comparison of the mean square control values for the different control laws at each stage for the Kuka robot.

Table 5. Comparison of the control integral values for the different control laws at each stage for the Kuka robot.

Data availability statement

The data that support the findings of this study are available from the corresponding author, [author initials], upon reasonable request.