Conference Paper

Dynamic Formation Reshaping Based on Point Set Registration in a Swarm of Drones

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

This work focuses on the formation reshaping in an optimized manner in autonomous swarm of drones. Here, the two main problems are: 1) how to break and reshape the initial formation in an optimal manner, and 2) how to do such reformation while minimizing the overall deviation of the drones and the overall time, i.e., without slowing down. To address the first problem, we introduce a set of routines for the drones/agents to follow while reshaping to a secondary formation shape. And the second problem is resolved by utilizing the temperature function reduction technique, originally used in the point set registration process. The goal is to be able to dynamically reform the shape of multi-agent based swarm in near-optimal manner while going through narrow openings between, for instance obstacles, and then bringing the agents back to their original shape after passing through the narrow passage using point set registration technique.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

Article
Full-text available
The focus of this work is to present a novel methodology for optimal distribution of a swarm formation on either side of an obstacle, when evading the obstacle, to avoid overpopulation on the sides to reduce the agents' waiting delays, resulting in a reduced overall mission time and lower energy consumption. To handle this, the problem is divided into two main parts: 1) the disturbance phase: how to morph the formation optimally to avoid the obstacle in the least possible time in the situation at hand, and 2) the convergence phase: how to optimally resume the intended formation shape once the threat of potential collision has been eliminated. For the first problem, we develop a methodology which tests different formation morphing combinations and finds the optimal one, by utilizing trajectory, velocity, and coordinate information, to bypass the obstacle. For the second problem, we utilize a thin-plate splines (TPS) inspired temperature function minimization method to bring the agents back from the distorted formation into the desired formation in an optimal manner, after collision avoidance has been successfully performed. Experimental results show that, in the considered test scenario, the proposed approach results in substantial energy savings as compared with the traditional methods.
Article
Full-text available
The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civil application domains, including real-time monitoring, providing wireless coverage, remote sensing, search and rescue, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. Smart UAVs are the next big revolution in the UAV technology promising to provide new opportunities in different applications, especially in civil infrastructure in terms of reduced risks and lower cost. Civil infrastructure is expected to dominate more than $45 Billion market value of UAV usage. In this paper, we present UAV civil applications and their challenges. We also discuss the current research trends and provide future insights for potential UAV uses. Furthermore, we present the key challenges for UAV civil applications, including charging challenges, collision avoidance and swarming challenges, and networking and security-related challenges. Based on our review of the recent literature, we discuss open research challenges and draw high-level insights on how these challenges might be approached.
Article
Full-text available
Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision avoidance systems (CAS). A lot of work is being done to make the CAS as safe and reliable as possible, necessitating a comparative study of the recent work in this important area. The paper provides a comprehensive review of collision avoidance strategies used for unmanned vehicles, with the main emphasis on unmanned aerial vehicles (UAV). It is an in-depth survey of different collision avoidance techniques that are categorically explained along with a comparative analysis of the considered approaches w.r.t. different scenarios and technical aspects. This also includes a discussion on the use of different types of sensors for collision avoidance in the context of UAVs.
Conference Paper
Full-text available
Collision avoidance in aerial environments using the conventional artificial potential field(APF) often faces local minima problems and the results prevent unmanned aerial vehicles(UAVs) from performing their missions. In addition, an UAV’s paths planned based on theconventional method are safe trajectories only in a certain static environment. To generateoptimal and collision-free paths in a dynamic environment, the authors propose a novel APFapproach, called “enhanced curl-free vector field”. For the repulsive potential field of theapproach proposed, one computes each angle between the velocity vectors of UAVs and therelative position vectors of moving obstacles to the UAVs. The comparisons of the computedangles and the velocity of UAVs determine the direction of the curl-free vector field. Resultsfrom two case simulations, static obstacles with local minima and dynamic obstacles, show thatour approach solves the local minima problems of path planning and generates more efficientpaths for avoiding potential collisions caused by dynamic obstacles compared to the existingAPF methods.
Article
Full-text available
Autonomous drones (also known as unmanned aerial vehicles) have several advantages over ground vehicles, including agility, swiftness, and energy-efficiency, and hence are convenient for light-weight delivery and substitutions for manned missions in remote operations. It is expected that autonomous drones will be deployed in diverse applications in near future. Typical drones are electric vehicles, powered by on-board batteries. This paper presents several contributions for automated battery-operated drone management systems: (1) We conduct an empirical study to model the battery performance of drones, considering various flight scenarios. (2) We study a joint problem of flight tour planning with recharging optimization for drones with an objective to complete a tour mission for a set of sites of interest. This problem captures diverse applications of delivery and remote operations by drones. (3) We implemented our optimization algorithms in an intelligent drone management system.
Article
Full-text available
This paper proposes a novel formation control strategy for nonholonomic intelligent vehicles based on virtual structure and consensus approach. The formation model is obtained based on the coordinate transformation and the virtual structure technique. The controllers are designed by using nonholonomic target tracking technique and leader-following consensus protocol. Depending on virtual structure approach and coordinate transformation, the formation control problem of multiple nonholonomic intelligent vehicles is converted into the target tracking and state consensus stabilization problem. Simulation and real-world experimental results show the correctness and effectiveness of the strategy.
Article
Full-text available
Target search and tracking is a classical but difficult problem in many research domains, including computer vision, wireless sensor networks and robotics. We review the seminal works that addressed this problem in the area of swarm robotics, which is the application of swarm intelligence principles to the control of multi-robot systems. Robustness, scalability and flexibility, as well as distributed sensing, make swarm robotic systems well suited for the problem of target search and tracking in real-world applications. We classify the works we review according to the variations and aspects of the search and tracking problems they addressed. As this is a particularly application-driven research area, the adopted taxonomy makes this review serve as a quick reference guide to our readers in identifying related works and approaches according to their problem at hand. By no means is this an exhaustive review, but an overview for researchers who are new to the swarm robotics field, to help them easily start off their research.
Conference Paper
Full-text available
The ability to integrate unmanned and manned aircraft into airspace is a critical capability that will enable growth in wide varieties of applications. Collision avoidance is a key enabler for the integration of manned and unmanned missions in civil and military operation theaters. Large efforts have been done to address collision avoidance problem to both manned and unmanned aircraft. However, there has been little comparative discussion of the proposed approaches. This paper presents a survey of the collision avoidance approaches those deployed for aircraft, especially for unmanned aerial vehicles. The collision avoidance concept is introduced together with proposing generic functions carried by collision avoidance systems. The design factors of the sense and avoid system, which are used to categorize methods, are explained deeply. Based on the design factors, several typical approaches are categorized.
Article
Full-text available
Point set registration is a key component in many computer vision tasks. The goal of point set registration is to assign correspondences between two sets of points and to recover the transformation that maps one point set to the other. Multiple factors, including an unknown nonrigid spatial transformation, large dimensionality of point set, noise, and outliers, make the point set registration a challenging problem. We introduce a probabilistic method, called the Coherent Point Drift (CPD) algorithm, for both rigid and nonrigid point set registration. We consider the alignment of two point sets as a probability density estimation problem. We fit the Gaussian mixture model (GMM) centroids (representing the first point set) to the data (the second point set) by maximizing the likelihood. We force the GMM centroids to move coherently as a group to preserve the topological structure of the point sets. In the rigid case, we impose the coherence constraint by reparameterization of GMM centroid locations with rigid parameters and derive a closed form solution of the maximization step of the EM algorithm in arbitrary dimensions. In the nonrigid case, we impose the coherence constraint by regularizing the displacement field and using the variational calculus to derive the optimal transformation. We also introduce a fast algorithm that reduces the method computation complexity to linear. We test the CPD algorithm for both rigid and nonrigid transformations in the presence of noise, outliers, and missing points, where CPD shows accurate results and outperforms current state-of-the-art methods.
Article
Full-text available
New reactive behaviors that implement formations in multirobot teams are presented and evaluated. The formation behaviors are integrated with other navigational behaviors to enable a robotic team to reach navigational goals, avoid hazards and simultaneously remain in formation. The behaviors are implemented in simulation, on robots in the laboratory and aboard DARPA's HMMWV-based unmanned ground vehicles. The technique has been integrated with the autonomous robot architecture (AuRA) and the UGV Demo II architecture. The results demonstrate the value of various types of formations in autonomous, human-led and communications-restricted applications, and their appropriateness in different types of task environments
Conference Paper
Distributed formation control and obstacle avoidance are two important challenges in autonomous navigation of a swarm of drones and can negatively affect each other due to possible competition that arises between them. In such a platform, a multi-priority control strategy is needed to be executed in each node to dynamically optimize the trade-offs between formation control and collision avoidance w.r.t. given system constraints, e.g. on energy and response time, by reordering priorities in run-time and choosing the appropriate formation and collision avoidance approach based on the state of the swarm, i.e., the kinematic parameters and geographical distribution of the nodes as well as the location of the observed obstacles. In this paper, we propose a method for formation/collision co-awareness with the goal of energy consumption and response time minimization. The algorithm is composed of two partial nested feedback-based control loops and based on three observations: 1) the relative location of the neighbor nodes for formation maintenance; 2) a boolean value indicating an observation of an obstacle by a local sensor, used for both formation control and collision avoidance; and 3) the distance of an obstacle to the node for collision avoidance in critical situations. The obtained comprehensive experimental results show that the proposed approach appropriately keeps the formation during the swarm’s travel in the presence of different obstacles.
Article
UAV swarm is a typical application of multi-agent system and consists of a certain number of single- or multi-function UAVs. This paper mainly focuses on the motion consensus and formation control of UAV swarm. A novel formation control algorithm suitable for both leaders and followers is designed, in which leaders are implicitly integrated into the swarm and can be influenced by navigational feedback from their flockmates. Theoretical analysis shows that the system is asymptotically stable and can converge to the desired formation without collision among vehicles. Numerical simulations are performed to illustrate the theoretical results and verify the velocity and trajectory tracking abilities of the algorithm. Results reveal that the proposed algorithm guarantees a swarm of UAVs to fly with predefined formation and track scheduled trajectory. Furthermore, the novel algorithm can reduce the communication consumption and enhance the adaptability and scalability of the system.
Article
Collision avoidance strategies for multiple UAVs (Unmanned Aerial Vehicles) based on geometry are investigated in this study. The proposed strategies allow a group of UAVs to avoid obstacles and separate if necessary through a simple algorithm with low computation by expanding the collision-cone approach to formation of UAVs. The geometric approach uses line-of-sight vectors and relative velocity vectors where dynamic constraints are included in the formation. Each UAV can determine which plane and direction are available for collision avoidance. An analysis is performed to define an envelope for collision avoidance, where angular rate limits and obstacle detection range limits are considered. Based on the collision avoidance envelope, each UAV in a formation determines whether the formation can be maintained or not while avoiding obstacles. Numerical simulations are performed to demonstrate the performance of the proposed strategies.
Article
In this paper, we consider the mobile robots formation control problem without direct measurement of the leader robot's linear velocity. Two decentralized nonlinear algorithms are proposed, respectively, based on adaptive dynamic feedback and immersion Rz invariance estimation based second order sliding mode control methodologies. The main idea is to solve formation problem by estimating the leader robots's linear velocity, while maintaining the given predefined separation distance and bearing angle between the leader robot and the follower robot. The stability of the closed-loop system is proven by means of the Lyapunov method. The proposed controllers are smooth, continuous and robust against unknown bounded uncertainties such as sensor inaccuracy between the outputs of sensors and the true values in collision free environments. Simulation examples and physical vehicles experiments are presented to verify the effectiveness of the proposed design approaches, and the proposed designed methodologies are carefully compared to illustrate the pros and cons of the approaches.
Article
The sense and avoid capability is one of the greatest challenges that has to be addressed to safely integrate unmanned aircraft systems into civil and nonsegregated airspace. This paper gives a review of existing regulations, recommended practices, and standards in sense and avoid for unmanned aircraft systems. Gaps and issues are identified, as are the different factors that are likely to affect actual sense and avoid requirements. It is found that the operational environment (flight altitude, meteorological conditions, and class of airspace) plays an important role when determining the type of flying hazards that the unmanned aircraft system might encounter. In addition, the automation level and the data-link architecture of the unmanned aircraft system are key factors that will definitely determine the sense and avoid system requirements. Tactical unmanned aircraft, performing similar missions to general aviation, are found to be the most challenging systems from an sense and avoid point of view, and further research and development efforts are still needed before their seamless integration into nonsegregated airspace.
Conference Paper
The airborne Sense and Avoid (SAA) problem is a challenging and complex optimal control problem to solve. This paper builds on the previous work by the authors,1 which focused on the methodology for formulating the airborne SAA problem as an optimal control problem. The focus of this current work is on how to realistically formulate the constraints associated with solving the airborne SAA problem as a nonlinear optimal control problem. Based on user defined cost functions, the objective of this optimization problem is to determine the optimal trajectory for an aircraft to y in order to avoid a collision. A fundamental necessity in solving the airborne collision avoidance problem is modeling and estimating the current and future trajectories of all potential intruder air- craft. To this end, this paper implements a 3D particle filter to model and estimate the intruder's nonlinear dynamic and measurement equations. As a result, the "point cloud" outputs of the particle filter realistically define 3D probability regions associated with the intruder's position at some (ti) time initial to some (tf) time final. The ability to accurately capture and model these probability regions as system constraints is essential in the formulation of the optimal control problem. The previous work by the authors assumed an underlying Gaussian distribution to model these probability regions; however, based on the nonlinearities associated with the system dynamics, the underlying distribution for these regions are not necessarily Gaussian. Therefore, this paper presents an alternate approach that does not assume any underlying distribution. This proposed approach efficiently captures the intruder's 3D probability regions as a convex optimization problem utilizing Khachiyan's Algorithm2, 3 and then smoothly interpolates between these probability regions to accurately identify "collision avoidance corridors" for the airborne SAA optimal control problem. This approach is demonstrated on a representative SAA scenario.
Conference Paper
At the current time the majority of small UAS are being used for military applications. There are many other applications for small UAS. Applications in the sciences are limited only by the availability of sensor systems light and small enough for the desired task. The two general measurement methodologies for UAS are either remote sensing or in-situ measurements. Remote sensing applications for small UAS run a wide range of possible applications most of which are currently in use on manned aircraft such as aerial imaging or LIDAR. In-situ measurements for UAS include atmospheric conditions, air quality applications, cloud moisture and airborne pathogens. New and emerging technologies suggest the shortly new sensors such as small SAR or new atmospheric chemistry applications will continue to open further veins of research to small UAS platforms. Copyright © 2009 by Gabriel B. Ladd. Published by the American Institute of Aeronautics and Astronautics, Inc.
Article
We present a survey of formation control of multi-agent systems. Focusing on the sensing capability and the interaction topology of agents, we categorize the existing results into position-, displacement-, and distance-based control. We then summarize problem formulations, discuss distinctions, and review recent results of the formation control schemes. Further we review some other results that do not fit into the categorization.
Conference Paper
In this paper three collision avoidance methods for an unmanned aerial vehicle (UAV) are tested and compared to one another. The quadrocopter dynamic model with attitude and velocity controller, a trajectory generator and a selection of collision avoidance approaches were implemented. The first collision avoidance method is based on a geometric approach which computes a direction of avoidance from the flight direction and simple geometric equations. The second technique uses virtual repulsive force fields causing the UAV to be repelled by obstacles. The last method is a grid-based online path re-planning algorithm with A* search that finds a collision free path during flight. Various flight scenarios were defined including static and dynamic obstacles.
Conference Paper
In this paper we first introduce a fundamental consensus algorithm for systems modeled by second-order dynamics. We then apply variants of the consensus algorithm to tackle formation control problems by appropriately choosing information states on which consensus is reached. Even in the absence of centralized leadership, the consensus based formation control strategies can guarantee accurate formation maintenance in the general case that information flow is unidirectional. We also show that existing leader-follower, behavioral, and virtual structure/virtual leader formation control approaches can be unified in the general framework of consensus building. A multi-vehicle formation control example is shown in simulation to illustrate our strategies
Conference Paper
In this paper, the synchronized position tracking controller is incorporated in formation flight control for multiple flying wings. With this technology, the performance and effectiveness of the formation controller are improved when the virtual structure approach is utilized to maintain formation geometry. Simulations are conducted on the nonlinear model of two flying wings to verify the proposed controller.
A new algorithm for non-rigid point matching
  • Haili Chui
  • A Rangarajan
Haili Chui, Rangarajan, A.: A new algorithm for non-rigid point matching. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662). vol. 2, pp. 44-51 vol.2 (June 2000)
Collision avoidance for uavs using reachable sets
  • Y Lin
  • S Saripalli
Lin, Y., Saripalli, S.: Collision avoidance for uavs using reachable sets. In: 2015 International Conference on Unmanned Aircraft Systems, ICUAS 2015. pp. 226-235. Institute of Electrical and Electronics Engineers Inc. (7 2015)
A summarization of collision avoidance techniques for autonomous navigation of uav
  • Akashdeep Payal
  • Raman Singh
Payal, Akashdeep, Raman Singh, C.: A summarization of collision avoidance techniques for autonomous navigation of uav. In: Jain, K., Khoshelham, K., Zhu, X., Tiwari, A. (eds.) Proceedings of UASG 2019. pp. 393-401. Springer International Publishing, Cham (2020)
Advances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection
  • J N Yasin
  • S A S Mohamed
  • M H Haghbayan
  • J Heikkonen
  • H Tenhunen
  • J Plosila
Yasin, J.N., Mohamed, S.A.S., Haghbayan, M.H., Heikkonen, J., Tenhunen, H., Plosila, J.: Navigation of autonomous swarm of drones using translational coordinates. In: Demazeau, Y., Holvoet, T., Corchado, J.M., Costantini, S. (eds.) Advances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection. pp. 353-362. Springer International Publishing, Cham (2020)