Design, dynamics and control of a fast two-wheeled quasiholonomic robot
Bibliographic record
Abstract
The control of wheeled mobile robots is particularly challenging because of the presence of nonholonomic constraints. Modern two-wheeled mobile robot control is further complicated by the presence of one unstable equilibrium point, which requires a continuous stabilization of the intermediate body by means of sensors. In order to simplify the control of these systems, Quasimoro, a novel two-wheeled mobile robot, is proposed. The control of Quasimoro is simplified by means of its mechanical design. The robot is designed for quasiholonomy, a property that simplifies the control of nonoholonomic systems. To further simplify the control, the robot is designed so as to have a stable equilibrium point. A nonholonomic robotic mechanical system that can be rendered quasiholonomic by control is termed, in this thesis, quasiholonomic. This is the case of Quasimoro. This work proposes a model-based design methodology for wheeled mobile robots, intended to decrease the development costs, under which the prototype is built only when the system requirements are fully met. Following this methodology, the proposed robot is then designed and prototyped. The conceptual design of the robot is undertaken by means of a detailed analysis of the most suitable drive systems and their layout. The mathematical model of the robot is formulated in the framework of the Lagrange formalism, by resorting to the concept of holonomy matrix, while the controllability analysis is conducted using modern tools from geometric control. The embodiment design entails the simulation of three virtual prototypes aimed at further simplifying the robot control. To this end, a robot drive system, based on the use of a timing belt transmission and a bicycle wheel, is designed, calibrated and tested. Due to Quasimoro's drive system, the stabilization of the intermediate body, a well-known challenge in two-wheeled mobile robot control, is achieved without the use of additional mechanical stabilizers---such as casters---or of sensors---such as gyros. The intended application of the proposed robot is the augmentation of wheelchair users, a field that tremendously benefits from the cost-effectiveness and control simplification of the system at hand. For purposes of validation, a full-scale proof-of-concept prototype of the robot is realized. Moreover, the robot functionality is demonstrated by means of motion control experiments.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".