Tracking control for non-holonomic mobile manipulator using decentralised control strategy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents a tracking control strategy for a non-holonomic mobile manipulator using a decentralised control strategy. The mobile manipulator is viewed as an interconnection of two subsystems - a non-holonomic mobile platform subsystem and a holonomic manipulator subsystem. First, a kinematic controller of the two-wheel driven mobile platform is developed to obtain a desired velocity. Second, a distributed control strategy is developed in order to track a desired trajectory in the joint space. This desired trajectory is obtained from the workspace trajectory using the inverse kinematics. The distributed control strategy consists of controlling the manipulator, starting from the last joint and going backwards until the first joint. Each joint is controlled while assuming that the remaining joints and the platform are stable and follow their desired trajectories. The stability of the system is proved using Lyapunov theory. These controllers are tested on a three degrees-of-freedom mobile manipulator and compared with the computed torque approach. The experimental and simulation results present a good tracking which shows the effectiveness of this control strategy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 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