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Extending our previous work in real-time vision-based Human Robot Interaction (HRI) with multi-robot systems, we present the first example of creating, modifying and commanding teams of UAVs by an uninstrumented human. To create a team the user focuses attention on an individual robot by simply looking at it, then adds or removes it from the current team(More)
In this paper we present two task-allocation strategies for a multi-robot transportation system. The first strategy is based on a centralized planner that uses domain knowledge to solve the assignment problem in linear time. In contrast in the second strategy, individual robots make rule-based allocation decisions using only locally obtainable information(More)
We examine the practical problem of a mobile autonomous robot performing a long-duration survey task, during which it must recharge its batteries periodically. We present a scalable, online, heuristic method that allows the robot to recharge efficiently, thus maximizing its rate of work. The method is a direct application of the rate-maximizing foraging(More)
We propose a novel method for non-uniform terrain coverage using Unmanned aerial vehicles (UAVs). The existing methods for coverage path planning consider a uniformly interesting target area and hence all the regions are covered with high resolution. However in many real world applications items of interest are not uniformly distributed but form patches of(More)
Energy is defined as the potential to perform work: every system that does some work must possess the required energy in advance. An interesting class of systems, including animals and recharging robots, has to actively choose when to obtain energy and when to dissipate energy in work. If working and collecting energy are mutually exclusive, as is common in(More)
We investigate the problem of a robot maximizing its long-term average rate of return on work. We present a means to obtain an estimate of the instantaneous rate of return when work is rewarded in discrete atoms, and a method that uses this to recursively maximize the long-term average return when work is available in localized patches, each with locally(More)
We describe a system whereby multiple humans and mobile robots interact robustly using a combination of sensing and signalling modalities. Extending our previous work on selecting an individual robot from a population by face-engagement, we show that reaching toward a robot - a specialization of pointing - can be used to designate a particular robot for(More)
We present a path planning method for MAVs with vision-only MonoSLAM that generates safe paths to a goal according to the information richness of the environment. The planner runs on top of monocular SLAM and uses the available information about structure of the environment and features visibility to find trajectories that maintain visual contact with(More)
We present a multi-modal multi-robot interaction whereby a user can identify an individual or a group of robots using haptic stimuli, and name them using a voice command (e.g."<i>You two are green</i>"). Subsequent commands can be addressed to the same robot(s) by name (e.g. "<i>Green! Take off</i>!"). We demonstrate this as part of a real-world integrated(More)