Advances in the control of autonomous systems have accompanied an expansion in the potential applications for autonomous robotic swarms. The success of applications involving humans depends on the quality of interaction with the swarm, particularly the trust that the commander places in the swarm. Absent from the literature is the design of commander trust dynamics that incorporate asymmetric responses to swarm performance. This paper focuses on developing an estimated trust model that employs a switched linear system structure. The identified model is used in a model-based observer that eliminates the need for self-reported trust measurements. Results from a recent user study with 51 participants illustrate considerations during the estimation of population parameters for such nonlinear model-based observers. It is anticipated that such a trust observer can be used to augment communication interfaces for human-swarm interactions in complex environments, leading to better performing systems incorporating humans in the loop.

We propose an algorithm for generating minimum-snap trajectories for quadrotors with linear computational complexity with respect to the number of segments in the spline trajectory. Our algorithm is numerically stable for large numbers of segments and is able to generate trajectories of more than 500, 000 segments. The computational speed and numerical stability of our algorithm makes it suitable for real-time generation of very large scale trajectories. We demonstrate the performance of our algorithm and compare it to existing methods, in which it is both faster and able to calculate larger trajectories than state-of-the-art. We also show the feasibility of the trajectories experimentally with a long quadrotor flight.

The paper considers the efficient selection of leader agents in a swarm running a distributed bearing-compass formation controller. The leaders apply external control which induces translation and scaling of the formation, providing manipulation methods useful to a human operator. The selection algorithm for maximizing translation and scale draws from modularity and submodularity theory. Consequently, the algorithms exhibit guaranteed optimal and suboptimal performance, respectively. For more restricted human-swarm interaction requiring pure translation and scale, a relaxed integer programming algorithm is described to reduce the combinatorial optimization problem to a computationally tractable semidefinite program. The leader selection strategies are supported through demonstration on a swarm testbed.

This paper examines an advection-based protocol for the coordination of a networked, multi-agent system. Diffusion forms the basis of the popular consensus dynamics and is closely related to advection. It is with this motivation that we examine a discretized version of advection over a network with the flow field realized through directed graph edges. We endeavor to demonstrate that the subsequent advection protocol forms an attractive set of system dynamics for coordinated control. This paper includes a formulation of the advection dynamics on directed graphs and a presentation of some of its characteristics. We also demonstrate the versatility of the advection dynamics with a decentralized load balancing application.

This paper examines the system dynamics of a networked multi-agent system, operating with a consensus-type algorithm, that can be influenced by external agents. We refer to this class of networks as semi-autonomous. We introduce a control scheme for such semi-autonomous networks, involving excitation of the network by the external agents, with the objective of manipulating or steering the network. In this context, we consider the situation where the external agents deliver a constant mean control signal. We proceed to examine the resultant mean and covariance of the network output and relate these quantities to circuit-theoretic notions of the network, quantifying the network's amenability to external signals. Four protocols for tree graphs, to promote and deter convergence and to increase and reduce average variance within the network are then presented. These protocols involve decentralized local edge swaps that can be performed in parallel and asynchronously.

This paper addresses the problem of communication range limitations for decentralized multi-vehicle mapping. We present a novel integrated communication and planning protocol that enables all vehicles to form a common global map. The fusion of mapping information is facilitated through the Information Filter and performed over a connected acyclic wireless communication network with limited communication range. The formation of the acyclic connected communication network is achieved by partitioning the landmark graph using graph theoretic tools during the planning phase. We provide results that illustrate the effectiveness of our approach over different distributions of landmarks.