This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas.

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A Survey on Aerial Swarm Robotics

A fundamental problem that the bearing rigidity theory studies is to determine when a framework can be uniquely determined up to a translation and a scaling factor by its inter-neighbor bearings While many previous works focused on the bearing rigidity of two-dimensional frameworks, a first contribution of this paper is to extend these results to arbitrary dimensions It is shown that a framework in an arbitrary dimension can be uniquely determined up to a translation and a scaling factor by the bearings if and only if the framework is infinitesimally bearing rigid In this paper, the proposed bearing rigidity theory is further applied to the bearing-only formation stabilization problem where the target formation is defined by inter-neighbor bearings and the feedback control uses only bearing measurements Nonlinear distributed bearing-only formation control laws are proposed for the cases with and without a global orientation It is proved that the control laws can almost globally stabilize infinitesimally bearing rigid formations Numerical simulations are provided to support the analysis

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Bearing Rigidity and Almost Global Bearing-Only Formation Stabilization

This paper describes the Robotarium — a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-robot research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium and discusses the considerations one must take when making complex hardware remotely accessible. In particular, safety must be built into the system already at the design phase without overly constraining what coordinated control programs users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.

/pdf/the-robotarium-a-remotely-accessible-swarm-robotics-research-jfnikj6svh.pdf

The Robotarium: A remotely accessible swarm robotics research testbed

It is well known that a multi-agent system (MAS) is a specific system consisting of multiple interacting autonomous agents. Consensus or synchronization, as one of the typical collective behaviors, is ubiquitous in nature. Over the last decades, consensus has been widely investigated in various disciplines, including mathematics, physics, biology, engineering, and social sciences. In particular, consensus of MAS with dynamical topology is an emerging new topic motivated by many real-world applications, such as wireless communication and sensor networks. However, the collective behavior of MAS with dynamical topology is very complex and cannot be easily analyzed by the traditional approaches. To resolve the issue of dynamical topology, various techniques and methods have been developed in the last decade. This paper aims to review the main advances in the consensus of MAS with dynamical topology, including several fundamental models and the corresponding methods. The main purpose is to promote this emerging topic on multi-agent systems, with emphasis on the interdisciplinary interest from the circuits and systems engineering communities.

Multi-Agent Systems with Dynamical Topologies: Consensus and Applications

This paper addresses passivity-based motion coordination of rigid bodies in the special Euclidean group SE(3) under the assumption that the agents exchange information over strongly connected graphs. In this paper, we especially focus on one of the motion coordination problems on SE(3) called attitude synchronization. We first develop a passivity-based distributed velocity input law to achieve attitude synchronization. Using the notion of algebraic connectivity, we then establish a connection between the speed of convergence and the structure of the interconnection graph. We also prove attitude synchronization in the leader-follower case and in the cases of communication delay and temporary communication failures. Finally, the performance of our developed control laws is demonstrated through both numerical simulation and experiments on a planar (2D) test bed.

Passivity-Based Attitude Synchronization in $SE(3)$

This paper addresses passivity-based pose synchronization in the Special Euclidean group SE(3) . We first develop a passivity-based distributed velocity input law to achieve pose synchronization. We next show that the pose synchronizes exponentially fast under an assumption on the initial states of the bodies, with an exponential convergence rate given by algebraic connectivity of interconnection graphs. We also prove pose synchronization in the presence of communication delays and topology switches. We moreover give further extensions of the present law, where desirable velocities and collision avoidance are taken into account. Finally, the effectiveness of the present inputs is demonstrated through numerical simulations and experiments on a planar (2D) test bed.

Y. Igarashi

Papers

Passivity-Based Attitude Synchronization in $SE(3)$

Passivity-Based Pose Synchronization in Three Dimensions