FPGA to study the behavior of a maneuvering UGV using sliding innovation filter
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
Field programmable gate arrays (FPGAs) are increasingly popular due to their customizability, which enables them to be tailored to specific applications, resulting in minimal resource usage that saves energy and space. In this work, we used an FPGA with a Z-board from Xilinx to simulate the application of the sliding innovation filter (SIF) to a robotic arm. SIF is a predictor-corrector filter used for both linear and nonlinear systems to estimate states and/or parameters. It shares similar principles with sliding mode observer and smooth variable structure filter (SVSF) and uses a correction gain derived to satisfy Lyapunov stability, keeping the estimates near the measurements. We tested SIF on a manipulator with two joints (rotational and prismatic), using FPGA to run the simulation while tracking resource utilization. We compared the results with those of SVSF.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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