Torrent details for "Li C. Assuring Safe Operation of Robotic Systems under Uncertain…" Log in to bookmark
Controls:
×
Report Torrent
Please select a reason for reporting this torrent:
Your report will be reviewed by our moderation team.
×
Report Information
Loading report information...
This torrent has been reported 0 times.
Report Summary:
| User | Reason | Date |
|---|
Failed to load report information.
×
Success
Your report has been submitted successfully.
Checked by:
Category:
Language:
None
Total Size:
8.8 MB
Info Hash:
5B687D5B13E94E01DB60F3CBF3C76BAAE2A89E4E
Added By:
Added:
Dec. 1, 2025, 3:15 a.m.
Stats:
|
(Last updated: Dec. 1, 2025, 3:16 a.m.)
| File | Size |
|---|---|
| Li C. Assuring Safe Operation of Robotic Systems under Uncertainty...2025.pdf | 8.8 MB |
Name
DL
Uploader
Size
S/L
Added
-
13.3 MB
[31
/
4]
2023-07-01
| Uploaded by indexFroggy | Size 13.3 MB | Health [ 31 /4 ] | Added 2023-07-01 |
-
20.2 MB
[44
/
3]
2024-12-03
| Uploaded by indexFroggy | Size 20.2 MB | Health [ 44 /3 ] | Added 2024-12-03 |
-
43.0 MB
[10
/
46]
2025-06-08
| Uploaded by andryold1 | Size 43.0 MB | Health [ 10 /46 ] | Added 2025-06-08 |
-
17.7 MB
[33
/
11]
2025-09-16
| Uploaded by andryold1 | Size 17.7 MB | Health [ 33 /11 ] | Added 2025-09-16 |
NOTE
SOURCE: Li C. Assuring Safe Operation of Robotic Systems under Uncertainty...2025
-----------------------------------------------------------------------------------
COVER
-----------------------------------------------------------------------------------
MEDIAINFO
Textbook in PDF format
Assuring Safe Operation of Robotic Systems under Uncertainty: Control and Learning Methods applies set-theoretic and reinforcement learning approaches to formulate, analyze, and solve the challenge of ensuring safe operation of robotic systems in an uncertain environment.
The authors adopt learning-supported, set-theoretic methods—specifically, the barrier Lyapunov function and the control barrier function—to achieve desirable robust safety with guaranteed performance in continuous-time nonlinear control applications. They also combine reinforcement learning with control theory to ensure safe learning and optimization. The reinforcement learning-based optimization framework incorporates safety and robustness guarantees by applying theoretical analysis tools from the field of control
×