Collision Avoidance Method for Self-Organizing Unmanned Aerial Vehicle Flights

This work was supported in part by the National Natural Science Foundation of China, China, under Grant 71601181, in part by the Young Talents Lifting Project, China, under Grant 17JCJQQT048, in part by the Huxiang Young Talents, China, under Grant 2018RS3079, and in part by the Complex Situational Cognitive Technology under Grant 315050202.Autonomous unmanned aerial vehicle (UAV) swarm flights have been investigated widely. In the presence of a high airspace density and increasingly complex flight conditions, collision avoidance between UAV swarms is very important; however, this problem has not been fully addressed, particularly among self-organizing flight clusters. In this paper, we developed a method for avoiding collisions between different types of self-organized UAV clusters in various flight situations. The Reynolds rules were applied to self-organized flights of UAVs and a parameter optimization framework was used to optimize their organization, before developing a collision avoidance solution for UAV swarms. The proposed method can self-organize the flight of each UAV swarm during the overall process and the UAV swarm can continue to fly according to the self-organizing rules in the collision avoidance process. The UAVs in the airspace all make decisions according to their individual type. The UAVs in different UAV swarms can merge in the same space while avoiding collisions, where the UAV's self-organized flight process and collision avoidance process are very closely linked, and the trajectory is smooth to satisfy the actual operational needs. The numerical and experimental tests were conducted to demonstrate the effectiveness of the proposed algorithm. The results confirmed the effectiveness of this approach where self-organized flight cluster collision avoidance was successfully achieved by the UAV swarms

Adaptive and learning-based formation control of swarm robots

Autonomous aerial and wheeled mobile robots play a major role in tasks such as search and rescue, transportation, monitoring, and inspection. However, these operations are faced with a few open challenges including robust autonomy, and adaptive coordination based on the environment and operating conditions, particularly in swarm robots with limited communication and perception capabilities. Furthermore, the computational complexity increases exponentially with the number of robots in the swarm. This thesis examines two different aspects of the formation control problem. On the one hand, we investigate how formation could be performed by swarm robots with limited communication and perception (e.g., Crazyflie nano quadrotor). On the other hand, we explore human-swarm interaction (HSI) and different shared-control mechanisms between human and swarm robots (e.g., BristleBot) for artistic creation. In particular, we combine bio-inspired (i.e., flocking, foraging) techniques with learning-based control strategies (using artificial neural networks) for adaptive control of multi- robots. We first review how learning-based control and networked dynamical systems can be used to assign distributed and decentralized policies to individual robots such that the desired formation emerges from their collective behavior. We proceed by presenting a novel flocking control for UAV swarm using deep reinforcement learning. We formulate the flocking formation problem as a partially observable Markov decision process (POMDP), and consider a leader-follower configuration, where consensus among all UAVs is used to train a shared control policy, and each UAV performs actions based on the local information it collects. In addition, to avoid collision among UAVs and guarantee flocking and navigation, a reward function is added with the global flocking maintenance, mutual reward, and a collision penalty. We adapt deep deterministic policy gradient (DDPG) with centralized training and decentralized execution to obtain the flocking control policy using actor-critic networks and a global state space matrix. In the context of swarm robotics in arts, we investigate how the formation paradigm can serve as an interaction modality for artists to aesthetically utilize swarms. In particular, we explore particle swarm optimization (PSO) and random walk to control the communication between a team of robots with swarming behavior for musical creation

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

Motion Planning of UAV Swarm: Recent Challenges and Approaches

The unmanned aerial vehicle (UAV) swarm is gaining massive interest for researchers as it has huge significance over a single UAV. Many studies focus only on a few challenges of this complex multidisciplinary group. Most of them have certain limitations. This paper aims to recognize and arrange relevant research for evaluating motion planning techniques and models for a swarm from the viewpoint of control, path planning, architecture, communication, monitoring and tracking, and safety issues. Then, a state-of-the-art understanding of the UAV swarm and an overview of swarm intelligence (SI) are provided in this research. Multiple challenges are considered, and some approaches are presented. Findings show that swarm intelligence is leading in this era and is the most significant approach for UAV swarm that offers distinct contributions in different environments. This integration of studies will serve as a basis for knowledge concerning swarm, create guidelines for motion planning issues, and strengthens support for existing methods. Moreover, this paper possesses the capacity to engender new strategies that can serve as the grounds for future work

Comprehensive review on controller for leader-follower robotic system

985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies

A Multi-UAV Clustering Strategy for Reducing Insecure Communication Range

Multi-unmanned aerial vehicle (UAV) flight formations can be deployed to monitor large areas. Individual UAVs communicate and exchange information while formation flying. but, such communication presents a security risk. The area between the UAV group range and the group communication range is called the insecurity range and in this region multi-UAV communication can cause serious information leakage. To resolve this problem, this paper considers two aspects, namely, cooperative control and secure communication. To implement cooperative control, a clustering algorithm is presented to accelerate the speed at which the multi-UAV formation converges. By setting the flight control factor to accelerate the convergence of multi-UAV, the UAV group forms a flock. To facilitate secure communication, the hierarchical virtual communication ring (HVCR) strategy is deployed to reduce the boundary of group communication and minimize the insecure range. The effectiveness of the clustering algorithm and HVCR strategy is demonstrated via theoretical analysis and experiments. In the case of 50 and 100 nodes, the results show that the clustering algorithm can facilitate multi-UAV group flocks. In the case of 25, 30, 35 and 40 nodes, the HVCR strategy can reduce the relative size of the insecure range to 65.33%, 62.95%, 61.50% and 60.55%, respectively

Solar-powered aquaponics prototype as sustainable approach for food production

This paper presents the establishment of a solar-powered aquaponics prototype as a sustainable, cost effective and environmentally sound approach for food production. In this study, a prototype bench top aquaponics rig with an integrated 20 W solar panel were fabricated for the cultivation of red Hybrid Tilapia (Oreochromis spp.) and leaf mustard (Brassica juncea). The size of the fish tank is about 29.5L and serves as the base for the setup. Additionally, the hydroponic grower compartment (0.45 m (L) � 0.32 m (W) � 0.13 m (H)) was stacked on top of the fish tank and was filled with LECA media bed for the plant growth. Two important operating parameters were studied. First, the amount of energy produced by the solar panel and the energy consumption by the water pump used in the setup. Secondly, the resultant effects from fish cultivation and plants growth on the water qualities and nitrification effi�ciency of the aquaponics unit. The aquaponics unit was operated for a month and the values of pH, tem�perature, and ammonia level were measured to be within the range of 6.4–7.2, 27.1–31.7 �C, and 1 mg�L�1 , respectively. Survival rate for fish was about 75% with specific growth rate (SGR) of 3.75% per day and food conversion ratio of about 1.15. A slight nutrient deficiency was evident and plants showed a healthy growth with height gain as high as 5 cm was achieved. Despite raining season, our data shows that the energy produced via 20 W solar panel enabled the unit to run at night without depending on local electricity for nearly two hours. Clearly, a larger solar panel is needed for longer operation. Nevertheless, the study has proven the potential of operating a low cost aquaponics setup using renew�able energy for a sustainable food production method

Constructing Dynamic Ad-hoc Emergency Networks using Software-Defined Wireless Mesh Networks

Natural disasters and other emergency situations have the potential to destroy a whole network infrastructure needed for communication critical to emergency rescue, evacuation, and initial rehabilitation. Hence, the research community has begun to focus attention on rapid network reconstruction in such emergencies; however, research has tried to create or improve emergency response systems using traditional radio and satellite communications, which face high operation costs and frequent disruptions. This thesis proposes a centralized monitoring and control system to reconstruct ad-hoc networks in emergencies by using software-defined wireless mesh networks (SDWMN). The proposed framework utilizes wireless mesh networks and software-defined networking to provide real-time network monitoring services to restore Internet access in a targeted disaster zone. It dispatches mobile devices including unmanned aerial vehicles and self-driving cars to the most efficient location aggregation to recover impaired network connections by using a new GPS position finder (GPS-PF) algorithm. The algorithm is based on density-based spatial clustering that calculates the best position to deploy one of the mobile devices. The proposed system is evaluated using the common open research emulator to demonstrate its efficiency and high accessibility in emergency situations. The results obtained from the evaluation show that the performance of the emergency communication system is improved considerably with the incorporation of the framework