Static Balancing of Spatial Parallel Platform Mechanisms—Revisited
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 article discusses the development of statically balanced spatial parallel platform mechanisms. A mechanism is statically balanced if its potential energy is constant for all possible configurations. This property is very important for robotic manipulators with large payloads, since it means that the mechanism is statically stable for any configuration, i.e., zero actuator torques are required whenever the manipulator is at rest. Furthermore, only inertial forces and moments have to be sustained while the manipulator is moving. The application that motivates this research is the use of parallel platform manipulators as motion bases in commercial flight simulators, where the weight of the cockpit results in a large static load. We first present a class of spatial parallel platform mechanisms that is suitable for static balancing. The class of mechanisms considered is a generalization of the manipulator described by Streit (1991, “Spatial Manipulator and Six Degree of Freedom Platform Spring Equilibrator Theory,” in Second National Conference on Applied Mechanisms and Robotics, VIII.B, pp. 1-1–1-6). Then sufficient conditions on the kinematic parameters that guarantee static balancing are derived for this class. Finally a particular mechanism is studied in more detail to show the practicability of its design. [S1050-0472(00)01401-X]
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) | 0.001 | 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) | 0.001 | 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 it