Route Planning of Unmanned Aerial Vehicles under Recharging and Mission Time Constraints

This paper investigates the problem of route planning for rechargeable unmanned aerial vehicles (UAV) under the mission time constraint in cases where more than one trip per round is required due to limited battery capacities. The goal is to determine the number of UAVs to be deployed and the flying paths that minimize the total mission cost. Unlike previous works, the electric cost incurred by UAV recharging proportional to actual flying distances is incorporated into our model. The problem is formulated as a mixed-integer programming model to minimize the sum of electric charging cost, the UAV usage cost, and the penalty cost from the violation of the mission time constraint. Extensive numerical experiments are conducted to examine the integrity and performance of the proposed model under various model parameters and deployment scenarios in grid areas and a real terrain area. The optimal solutions can be obtained for small-scale problem instances in a reasonable runtime. For large-scale problems, only feasible solutions can be obtained due to limited computational resources.

Joint Optimization on Trajectory, Cache Placement, and Transmission Power for Minimum Mission Time in UAV-Aided Wireless Networks

In recent years, due to the strong mobility, easy deployment, and low cost of unmanned aerial vehicles (UAV), great interest has arisen in utilizing UAVs to assist in wireless communication, especially for on-demand deployment in emergency situations and temporary events. However, UAVs can only provide users with data transmission services through wireless backhaul links established with a ground base station, and the limited capacity of the wireless backhaul link would limit the transmission speed of UAVs. Therefore, this paper designed a UAV-assisted wireless communication system that used cache technology and realized the transmission of multi-user data by using the mobility of UAVs and wireless cache technology. Considering the limited storage space and energy of UAVs, the joint optimization problem of the UAV’s trajectory, cache placement, and transmission power was established to minimize the mission time of the UAV. Since this problem was a non-convex problem, it was decomposed into three sub-problems: trajectory optimization, cache placement optimization, and power allocation optimization. An iterative algorithm based on the successive convex approximation and alternate optimization techniques was proposed to solve these three optimization problems. Finally, in the power allocation optimization, the proposed algorithm was improved by changing the optimization objective function. Numerical results showed that the algorithm had good performance and could effectively reduce the task completion time of the UAV.

Multi-USV Adaptive Exploration Using Kernel Information and Residual Variance

Using a team of robots for estimating scalar environmental fields is an emerging approach. The aim of such an approach is to reduce the mission time for collecting informative data as compared to a single robot. However, increasing the number of robots requires coordination and efficient use of the mission time to provide a good approximation of the scalar field. We suggest an online multi-robot framework m-AdaPP to handle this coordination. We test our framework for estimating a scalar environmental field with no prior information and benchmark the performance via field experiments against conventional approaches such as lawn mower patterns. We demonstrated that our framework is capable of handling a team of robots for estimating a scalar field and outperforms conventional approaches used for approximating water quality parameters. The suggested framework can be used for estimating other scalar functions such as air temperature or vegetative index using land or aerial robots as well. Finally, we show an example use case of our adaptive algorithm in a scientific study for understanding micro-level interactions.

Sistem Kontrol Robot Sepak Bola Beroda menggunakan Finite State Machine (FSM)

ABSTRAKPerkembangan teknologi menuntut transisi alat yang berbasis manual menjadi otomatis. Hal ini tak terkecuali pada perkembangan robot, termasuk robot sepak bola. Robot ini mengalami perkembangan sangat pesat. Hal ini didukung dengan adanya Kontes Robot Sepak Bola Indonesia (KRSBI). Penelitian kali mengusulkan robot sepak bola beroda dengan omni-directional weel sebagai pergrakannya menggunakan Finite State Machine (FSM) sebagai metode kontrol untuk menjalankan misi yang ditentukan. Misi robot yang dikembangkan yaitu mencari bola (wander), mencari posisi lurus terhadap bola, mencari gawang, dan menendang bola. Robot ini menggunakan CMUCam5 sebagai sensor masukan untuk mendeteksi bola sebagai target bedasarkan warna dan jarak. Jarak yang digunakan yaitu antara 20 cm sampai 60 cm dengan sudut antara -40 derajat sampai 40 derajat dan intensitas cahaya antara 113 sampai 1213 lux. Implementasi FSM pada robot sepak bola beroda dengan 5 jenis percobaan mencapai tingkat keberhasilan yang bagus yaitu 86% dengan rata-rata waktu menjalankan misi 29.24 detik.Kata kunci: CMUCam5, Finite State Machine, Omni-directional wheel, Robot Sepak Bola ABSTRACTTechnological development demands a transition from manual to automatic tools. It includes soccer robots that have developed so rapidly. This development is supported by the Indonesian Football Robot Contest (KRSBI). This study proposes a wheeled soccer robot with Omni-directional weel as its movement using Finite State Machine (FSM) as a control to carry out the specified mission. The mission is wandering to seek the ball, looking for a straight position to the ball, looking for the goal, and kicking the ball. This robot uses CMUCam5 as an input to detect the ball as a target based on color and distance. The distance used is between 20-60 cm with an angle of -40 degree to 40 degree and light intensity between 113-1213 lux. The implementation of FSM on a wheeled soccer robot with five types of experiments achieved a good result of 86% with an average mission time of 29.24 seconds.Keywords: CMUCam5, Finite State Machine, Omni-directional weel, Wheeledsoccer robot

Helicopter Hoist Performance in Novice and Experienced Hoist Operators

BACKGROUND: Helicopter hoist operators are highly skilled and critical crewmembers in search and rescue. However, hoist operator training programs are relatively underdeveloped in comparison to helicopter pilot training. It is critical that this simulator teaches the necessary skills for high-level performance given the dangers associated with helicopter hoist operation. As a result, we sought to validate and identify critical aspects of skilled hoisting.METHODS: Through expert consultation, we identified several measures of hoist operation, such as mission time, cable plumb, cable tension, cable hand position, and cable displacement. We compared hoist performance between experienced and novice hoist operators in a simulated hoisting mission with two levels of difficulty (with and without wind). The experienced group (eight men/one woman) was composed of nine active or former military hoist operators who were working in commercial search and rescue. The novice group was composed of seven subjects (two men/five women) from the general population and had no previous experience with hoisting operations or the simulator.RESULTS: We found that experienced hoist operators had faster mission time, similar cable plumb, lower tension, and less variable hand position. Further, experienced hoist operators pulled the cable inward in the wind while novice hoist operators pushed the cable away.DISCUSSION: These findings suggests that this simulator captures performance differences between skill levels and, as a result, is a first step supporting the use of this simulator for hoist operator training.King MT, Lenser S, Rogers D, Carnahan H. Helicopter hoist performance in novice and experienced hoist operators. Aerosp Med Hum Perform. 2020; 91(6):496–500.