MA41572B1 - Autonomous navigation and behavior of unmanned vehicle without connection to the control station - Google Patents
Autonomous navigation and behavior of unmanned vehicle without connection to the control stationInfo
- Publication number
- MA41572B1 MA41572B1 MA41572A MA41572A MA41572B1 MA 41572 B1 MA41572 B1 MA 41572B1 MA 41572 A MA41572 A MA 41572A MA 41572 A MA41572 A MA 41572A MA 41572 B1 MA41572 B1 MA 41572B1
- Authority
- MA
- Morocco
- Prior art keywords
- mission
- connection
- behavior
- decision
- control station
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/0088—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/20—Control system inputs
- G05D1/22—Command input arrangements
- G05D1/228—Command input arrangements located on-board unmanned vehicles
Landscapes
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Aviation & Aerospace Engineering (AREA)
- Health & Medical Sciences (AREA)
- Business, Economics & Management (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Game Theory and Decision Science (AREA)
- Medical Informatics (AREA)
- Traffic Control Systems (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
Les systèmes de dècision autonomes qui sont utilisés dans les avions sans pilotes sont conçus pour gérer des imprévus tels que la perte de connexion. Dans un tel cas, selon l'implémentation du système, celui-ci exécute un retour à la base en essayant de minimiser les risques, sinon, il veille à continuer l'exécution de la mission avec un mécanisme de cycles d'évaluations et de corrections le temps que la connexion soit rétablie. Ces implémentations, par leurs conceptions, permettent au système de fonctionner avec des performances définies par défaut sans qu'ils ne soient capables de prendre des initiatives, changer de mission en vol, gérer les situations d'incertitude, ni être totalement indépendants d'une station de contrôle. Nous proposons un système et méthode avec une conception où le fonctionnement en autonomie décisionnelle est le moyen principal d'opérer l'avion sans pilote pendant toute la mission, incluant le décollage et l'atterrissage. La commande à distance depuis une station au sol est secondaire. Cette autonomie décisionnelle est implémentée par trois modules de comportement, de vision et de mission dont l'implémentation et le fonctionnement sont décrit dans ce document.Autonomous decision systems that are used in unmanned aircraft are designed to deal with unforeseen events such as loss of connection. In such a case, depending on the implementation of the system, it performs a return to base trying to minimize the risks, otherwise, it ensures to continue the execution of the mission with a mechanism of cycles of evaluations and corrections while the connection is reestablished. These implementations, by their designs, allow the system to operate with performance defined by default without being able to take initiatives, change mission in flight, manage situations of uncertainty, or be completely independent of a control station. We propose a system and method with a design where decision-making autonomy is the primary means of operating the unmanned aircraft during the entire mission, including take-off and landing. Remote control from a ground station is secondary. This decision-making autonomy is implemented by three behavior, vision and mission modules, the implementation and operation of which are described in this document.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| MA41572A MA41572B1 (en) | 2017-12-05 | 2017-12-05 | Autonomous navigation and behavior of unmanned vehicle without connection to the control station |
| PCT/MA2018/050013 WO2019112407A1 (en) | 2017-12-05 | 2018-12-04 | Autonomous pilotless vehicle navigation and behaviour without connection to the control station |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| MA41572A MA41572B1 (en) | 2017-12-05 | 2017-12-05 | Autonomous navigation and behavior of unmanned vehicle without connection to the control station |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| MA41572A1 MA41572A1 (en) | 2019-06-28 |
| MA41572B1 true MA41572B1 (en) | 2019-08-30 |
Family
ID=65019551
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| MA41572A MA41572B1 (en) | 2017-12-05 | 2017-12-05 | Autonomous navigation and behavior of unmanned vehicle without connection to the control station |
Country Status (2)
| Country | Link |
|---|---|
| MA (1) | MA41572B1 (en) |
| WO (1) | WO2019112407A1 (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111353606B (en) * | 2020-02-29 | 2022-05-03 | 中国电子科技集团公司第五十二研究所 | Deep reinforcement learning air combat game method and system based on fuzzy decision tree |
| CN111914412B (en) * | 2020-07-21 | 2023-07-04 | 同济大学 | A fault injector-based automatic driving performance limitation testing system and method |
| CN112099525B (en) * | 2020-08-31 | 2021-10-15 | 北京航空航天大学 | A coordinated control method for maintaining low communication connectivity for spacecraft formation flight |
| CN113110114B (en) * | 2021-05-24 | 2023-07-14 | 北京润科通用技术有限公司 | Scheduling method and device for super-real-time joint simulation |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7512462B2 (en) | 2004-11-16 | 2009-03-31 | Northrop Grumman Corporation | Automatic contingency generator |
| US8078319B2 (en) | 2005-02-16 | 2011-12-13 | Lockheed Martin Corporation | Hierarchical contingency management system for mission planners |
| EP2745180A4 (en) * | 2011-08-16 | 2015-09-02 | Unmanned Innovation Inc | MODULAR FLIGHT MANAGEMENT SYSTEM INCORPORATING AN AUTOMATIC PILOT |
| DE112013001597T5 (en) * | 2012-03-22 | 2014-12-11 | Israel Aerospace Industries Ltd. | Planning and monitoring of autonomous mission |
| JP6278539B2 (en) * | 2014-09-05 | 2018-02-14 | エスゼット ディージェイアイ テクノロジー カンパニー リミテッドSz Dji Technology Co.,Ltd | Flight mode selection based on situation |
| US9715235B2 (en) | 2015-06-05 | 2017-07-25 | The Boeing Company | Autonomous unmanned aerial vehicle decision-making |
-
2017
- 2017-12-05 MA MA41572A patent/MA41572B1/en unknown
-
2018
- 2018-12-04 WO PCT/MA2018/050013 patent/WO2019112407A1/en not_active Ceased
Also Published As
| Publication number | Publication date |
|---|---|
| WO2019112407A1 (en) | 2019-06-13 |
| MA41572A1 (en) | 2019-06-28 |
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