Adaptive backstepping control approach for the trajectory tracking of mobile manipulators
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Bibliographic record
Abstract
This paper presents a novel adaptive backstepping controller for n + m degrees of freedom (DOF) mobile manipulator with the aim of simultaneous control of the velocity of the mobile platform and the motion of the end-effector. Using the idea of kinematic backstepping control and adaptive torque control, a two-step controller is presented for the nonholonomic mobile manipulator. A kinematic velocity control is designed in the first step such that all the desired trajectories are achieved. In the second step, the adaptive torque controller based on the dynamics of the mobile manipulator is designed such that the mobile platform velocity and the end-effector position converge to the reference trajectories designed in the first step. This control scheme provides an efficient solution to the motion control problem of mobile manipulators and the simulation results verify the effectiveness of the proposed control design.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it