Robust control design for teleoperation of multiple mobile manipulators under time delays
Bibliographic record
Abstract
Summary This article addresses a novel multilateral teleoperation control scheme for single‐master multiple slave systems, which can be extended to n masters and n slaves without the loss of generality, where the master is a m degrees of freedom (DOF) manipulator arm and the slaves are m DOF mobile manipulators. The human operator operates the master robot to remotely control the slaves handling a target object. The master position signal is transmitted to the slave side to generate a desired object trajectory as well as the reference mobile base velocity. An adaptive robust controller is designed for the slaves to follow the desired trajectory from the master, which not only provides the excellent trajectory tracking but also optimize the internal force distribution of the object. A null space controller is designed for the mobile platforms of the mobile manipulators to achieve the velocity consensus while achieving the main task of object transportation. The novel control design uses the transmission of the environmental force feedback over the communication channel by the estimated parameters of the environment, which helps retain the stability of the overall system. The environmental force is predicted on the master side based on the estimated environmental parameters. The proposed control design can simultaneously achieve the objectives of stability, synchronization, and optimal internal force distribution. The simulation results of a single‐master and three slaves teleoperation system validate the efficacy of the proposed control algorithm.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".