Energy-efficient route planning for autonomous aerial vehicles based on graph signal recovery

This paper designs a spatial data-centric tour and charging scheduler for electric vehicles, which need energy-efficient route planning, especially when visiting multiple destinations, due to their short driving range. Basically, the hybrid orienteering problem solver finds a feasible tour schedule for mandatory user-selected tour spots and optimal system-recommended charging spots, aiming at reducing the waiting time and meeting the given constraint. To recommend essential candidates, our system manages the information on tour spots and charging facilities in the spatial database, adjusting the bounding box size according to the pre-analysis result. The pre-analysis module can implement a sophisticated recommendation logic based on the preprocessed data customized mainly from geographic analysis. In addition, by continuously updating the current status of each charger, the recommender can catch the installation of new charging facilities and exclude the failed or overbooked chargers.

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On the way to a multi-modal energy-efficient route

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society ◽

10.1109/iecon.2013.6699908 ◽

2013 ◽

Cited By ~ 4

Author(s):

Matthias Prandtstetter ◽

Markus Straub ◽

Jakob Puchinger

Keyword(s):

Energy Efficient ◽

Efficient Route ◽

The Way

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Autonomous Loitering Control for a Flapping Wing Miniature Aerial Vehicle With Independent Wing Control

Volume 5A: 38th Mechanisms and Robotics Conference ◽

10.1115/detc2014-34752 ◽

2014 ◽

Cited By ~ 4

Author(s):

Luke Roberts ◽

Hugh A. Bruck ◽

Satyandra K. Gupta

Keyword(s):

Energy Efficient ◽

Pid Controller ◽

Control Algorithm ◽

Flapping Wing ◽

Flight Testing ◽

Response Error ◽

Aerial Vehicles ◽

Aerial Vehicle

Flapping wing miniature aerial vehicles (FWMAVs) offer advantages over traditional fixed wing or quadrotor MAV platforms because they are more maneuverable than fixed wing aircraft and are more energy efficient than quadrotors, while being quieter than both. Currently, autonomy in FWMAVs has only been implemented in flapping vehicles without independent wing control, limiting their level of control. We have developed Robo Raven IV, a FWMAV platform with independently controllable wings and an actuated tail controlled by an onboard autopilot system. In this paper, we present the details of Robo Raven IV platform along with a control algorithm that uses a GPS, gyroscope, compass, and custom PID controller to autonomously loiter about a predefined point. We show through simulation that this system has the ability to loiter in a 50 meter radius around a predefined location through the manipulation of the wings and tail. A simulation of the algorithm using characterized GPS and tail response error via a PID controller is also developed. Flight testing of Robo Raven IV demonstrated the success of this platform, even in winds of up to 10 mph.

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Trust-Enabled Energy Effective Optimal Framework for Detection of Intrusions in the Network Using AI Scheme

10.21203/rs.3.rs-906210/v1 ◽

2021 ◽

Author(s):

Putty Srivi ◽

Lavadya Nirmala Devi

Keyword(s):

Data Transmission ◽

Energy Efficient ◽

Data Dissemination ◽

Cuckoo Search ◽

Biologically Inspired ◽

Nodal Distance ◽

End To End Delay ◽

Short Period ◽

Secure Data Transmission ◽

Efficient Route

Abstract Wireless Sensor Networks (WSN) are self-possessed of the devices that are capable of actuating/sensing, processing, and communicating. This is employed for enhancing the day-to-day life, moreover secure data transmission was regarded as the major challenging aspect for the deployment of data. Data dissemination is a crucial in the complex communications framework for transferring messages for any given condition on the network. The dilemma of fixing the safest efficient route was a tedious issue. Hence the secure and most reliable way will give the appropriate solution for the routing issues. Here in this paper the Trust based energy efficient route path identification by Multi-faceted biologically-inspired probabilistic Cuckoo search Node optimization algorithm (TEERP-MFBPCS)is employed to find the efficient safest route within a short period. After seeing the efficient route, the node can be distinguished upon the traffic and security. Then in the selected route, the nodal distance can be calculated through applying weighted-biased end-to-end delay-based approach for traffic analysis. Finally, the intrusion node can be detected and the performance analysis is carried.

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