A binary gridding path-planning method for plant-protecting UAVs on irregular fields

The use of plant-protecting unmanned aerial vehicles(UAVs)for pesticide spraying is an essential operation in modern agriculture.The balance between reducing pesticide consumption and energy consumption is a significant focus of current research in the path-planning of plant-protecting UAVs.In this study,we proposed a binarization multi-objective model for the irregular field area,specifically an improved non-dominated sorting genetic algorithm–II based on the knee point and plane measurement(KPPM-NSGA-ii).The binarization multi-objective model is applied to convex polygons,concave polygons and fields with complex terrain.The experiments demonstrated that the proposed KPPM-NSGA-ii can obtain better results than the unplanned path method whether the optimization of pesticide consumption or energy consumption is preferred.Hence,the proposed algorithm can save energy and pesticide usage and improve the efficiency in practical applications.

Path Planning for AUVs Based on Improved APF-AC Algorithm

With the increase in ocean exploration activities and underwater development,the autonomous underwater vehicle(AUV)has been widely used as a type of underwater automation equipment in the detection of underwater environments.However,nowadays AUVs generally have drawbacks such as weak endurance,low intelligence,and poor detection ability.The research and implementation of path-planning methods are the premise of AUVs to achieve actual tasks.To improve the underwater operation ability of the AUV,this paper studies the typical problems of path-planning for the ant colony algorithm and the artificial potential field algorithm.In response to the limitations of a single algorithm,an optimization scheme is proposed to improve the artificial potential field ant colony(APF-AC)algorithm.Compared with traditional ant colony and comparative algorithms,the APF-AC reduced the path length by 1.57%and 0.63%(in the simple environment),8.92%and 3.46%(in the complex environment).The iteration time has been reduced by approximately 28.48%and 18.05%(in the simple environment),18.53%and 9.24%(in the complex environment).Finally,the improved APF-AC algorithm has been validated on the AUV platform,and the experiment is consistent with the simulation.Improved APF-AC algorithm can effectively reduce the underwater operation time and overall power consumption of the AUV,and shows a higher safety.

Survey of Safety Management Approaches to Unmanned Aerial Vehicles and Enabling Technologies

Unmanned aerial vehicle(UAV)has a rapid development over the last decade.However,an increasing number of severe flight collision events caused by explosive growth of UAV have drawn widespread concern.It is an important issue to investigate safety management approaches of UAVs to ensure safe and efficient operation.In this paper,we present a comprehensive overview of safety management approaches in large,middle and small scales.In large-scale safety management,path-planning problem is a crucial issue to ensure safety and ordered operation of UAVs globally.In middle-scale safety management,it is an important issue to study the conflict detection and resolution methods.And in small-scale safety management,real-time collision avoidance is the last line of ensuring safety.Moreover,a UAV can be regarded as a terminal device connected through communication and information network.Therefore,the enabling technologies,such as sensing,command and control communication,and collaborative decision-making control technology,have been studied in the last.

Autonomous energy efficient wheel loader research at TUT

Future worksites will be occupied by different level of automation work machines. How these machines are working individually and how a fleet of these machines cooperates will be in focus of research and development work in the future. In this paper the studied off-road vehicle is a wheel loader. It can be controlled manually, remotely or autonomously. The control strategy of autonomous wheel loader is consisting of, e.g., static and dynamic mapping, path planning, obstacle observation and avoidance. In the autonomous machines and also in machines where operator assistance system is active the situational awareness is the key research field. Power management in hydraulic work machines are still active fields of research. Multiple architectures and configurations have been suggested concerning this area. In addition, implemented solutions that consider an entire machine are rarely presented. This paper introduces the research work of the control systems which are minimising the fuel consumption.