We demonstrate that structured light-based depth sensing with standard perception algorithms can enable mobile peer-to-peer interaction between humans and robots. We posit that the use of recent emerging devices for depth-based imaging can enable robot perception of non-verbal cues in human movement in the face of lighting and minor terrain variations. Toward this end, we have developed an integrated robotic system capable of person following and responding to verbal and non-verbal commands under varying lighting conditions and uneven terrain. The feasibility of our system for peer-to-peer HRI is demonstrated through two trials in indoor and outdoor environments.

To enable the successful deployment of task-achieving multi-robot systems (MRS), coordination mechanisms must be utilized in order to effectively mediate the interactions between the robots and the task environment. Over the past decade, there have been a number of elegant experimentally demonstrated MRS coordination mechanisms. Most of these mechanisms have been task-specific in nature, typically providing only empirical insights into coordination design and little in the way of systematic techniques to assist in the design of coordinated MRS for new task domains. To fully realize the potentials of MRS, formally-grounded systematic techniques amenable to analysis are needed in order to facilitate the design of coordinated MRS. We address this problem by presenting a formal framework for describing and reasoning about coordination in a MRS. Using this principled foundation, we are developing a suite of general methods for automatically synthesizing the controllers of robots constituting a MRS such that the given task is performed in a coordinated fashion. This paper presents a method for the automatic synthesis of a specific type of controller, one that is stateless but capable of inter-robot communication. We also present a graph coloring-based approach for minimizing the number of necessary unique communication messages. The synthesis of such communicative controllers provides a means for assessing the uses and limitations of communication in MRS coordination. We present experimental validation of our formal approach of controller synthesis in a multi-robot construction domain through physically-realistic simulations and in real-robot demonstrations.

In this paper we present a method by which to organize the interactions of autonomous assembly agents in intelligent self-assembly (ISA). Each assembly agent has limited and local sensing and local rule-based control. A transition rule set (TRS) compiler is presented which takes a desired goal structure as input and gives as output a set of rules. When each assembly agent utilizes these rules, the desired goal structure is assembled. We show that the TRS compiler is scalable, efficient, and is capable of producing rules for a large class of goal structures.

A large-scale minimalist multi-robot system (LMMS) is one composed of a group of robots each with limited capabilities in terms of sensing, computation, and communication. Such systems have received increased attention due to their empirically demonstrated performance and beneficial characteristics, such as their robustness to environmental perturbations and individual robot failure and their scalability to large numbers of robots. However, little work has been done in investigating ways to endow such a LMMS with the capability to achieve a desired division of labor over a set of dynamically evolving concurrent tasks, important in many task-achieving LLMS. Such a capability can help to increase the efficiency and robustness of overall task performance as well as open new domains in which LMMS can be seen as a viable alternative to more complex control solutions. In this paper, we present a method for achieving a desired division of labor in a LMMS, experimentally validate it in a realistic simulation, and demonstrate its potential to scale to large numbers of robots and its ability to adapt to environmental perturbations.