Abstract:
Unmanned and autonomous vehicles (UxV) are one of most attractive and important technologies for many kinds of applications. A lot of researches related to multi UxVs hav...Show MoreMetadata
Abstract:
Unmanned and autonomous vehicles (UxV) are one of most attractive and important technologies for many kinds of applications. A lot of researches related to multi UxVs have been made enthusiastically for the last several decades because there is a trend to use those UxVs as a swarm. When the algorisms are implemented in UxVs for real operations, the algorism must adapt to a lot of unexpected environmental changes and events occurred in the real world. In general, it is difficult that an algorism reconciles the adaptability and optimization for a mission. In this context, we have been investigated the adaptive mechanism inspired by living organisms and realized a new control algorism called as “Autonomous and adaptive control”. This proposed algorism reconciles adaptability and ability of optimization for a mission of multi UxVs. In this paper, we apply the algorism to a use case of target tracking. It was confirmed that our algorism achieve most optimal operation in comparison of conventional algorisms with respect to energy consumption of the operation and the defense ability while keeping high detection ability. We also think that our algorism will be used for a lot of other use cases with multi UxVs.
Published in: 2016 IEEE/OES Autonomous Underwater Vehicles (AUV)
Date of Conference: 06-09 November 2016
Date Added to IEEE Xplore: 12 December 2016
ISBN Information:
Electronic ISSN: 2377-6536
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Adaptive Control ,
- Autonomic Control ,
- Environmental Changes ,
- Autonomous Vehicles ,
- Optimal Operation ,
- Detection Ability ,
- Unexpected Changes ,
- Target Tracking ,
- Kinds Of Applications ,
- Lot Of Changes ,
- Lot Of Cases ,
- Intrusion ,
- Area Ratio ,
- Operation Time ,
- Target Location ,
- Target Area ,
- Average Probability ,
- Nonlinear Programming ,
- State Machine ,
- Autonomous Surface Vehicles ,
- Search Effort ,
- Blind Area ,
- Specific Rules ,
- Mixed-integer Nonlinear Programming ,
- Probability Of Finding ,
- Special Areas ,
- Amount Of Movement
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Adaptive Control ,
- Autonomic Control ,
- Environmental Changes ,
- Autonomous Vehicles ,
- Optimal Operation ,
- Detection Ability ,
- Unexpected Changes ,
- Target Tracking ,
- Kinds Of Applications ,
- Lot Of Changes ,
- Lot Of Cases ,
- Intrusion ,
- Area Ratio ,
- Operation Time ,
- Target Location ,
- Target Area ,
- Average Probability ,
- Nonlinear Programming ,
- State Machine ,
- Autonomous Surface Vehicles ,
- Search Effort ,
- Blind Area ,
- Specific Rules ,
- Mixed-integer Nonlinear Programming ,
- Probability Of Finding ,
- Special Areas ,
- Amount Of Movement
- Author Keywords