Brian P. Gerkey

Sold!: auction methods for multirobot coordination

The key to utilizing the potential of multirobot systems is cooperation. How can we achieve cooperation in systems composed of failure-prone autonomous robots operating in noisy, dynamic environments? We present a method of dynamic task allocation for groups of such robots. We implemented and tested an auction-based task allocation system which we call MURDOCH, built upon a principled, resource centric, publish/subscribe communication model. A variant of the Contract Net Protocol, MURDOCH produces a distributed approximation to a global optimum of resource usage. We validated MURDOCH in two very different domains: a tightly coupled multirobot physical manipulation task and a loosely coupled multirobot experiment in long-term autonomy. The primary contribution of the paper is to show empirically that distributed negotiation mechanisms such as MURDOCH are viable and effective for coordinating physical multirobot systems.

Most valuable player: a robot device server for distributed control

Successful distributed sensing and control require data to flow effectively between sensors, processors and actuators on single robots, in groups and across the Internet. We propose a mechanism for achieving this flow that we have found to be powerful and easy to use; we call it Player. Player combines an efficient message protocol with a simple device model. It is implemented as a multithreaded TCP socket server that provides transparent network access to a collection of sensors and actuators, often comprising a robot. The socket abstraction enables platform- and language-independent control of these devices, allowing the system designer to use the best tool for the task at hand Player is freely available from http://robotics.usc.edu/player.

Multi-robot task allocation: analyzing the complexity and optimality of key architectures

Important theoretical aspects of multi-robot coordination mechanisms have, to date, been largely ignored. To address part of this negligence, we focus on the problem of multi-robot task allocation. We give a formal, domain-independent, statement of the problem and show it to be an instance of another, well-studied, optimization problem. In this light, we analyze several recently proposed approaches to multi-robot task allocation, describing their fundamental characteristics in such a way that they can be objectively studied, compared, and evaluated.

On device abstractions for portable, reusable robot code

We seek to make robot programming more efficient by developing a standard abstract interface for robot hardware, based on familiar techniques from operating systems and network engineering. This paper describes the application of three well known abstractions, the character device model, the interface/driver model, and the client/server model to this purpose. These abstractions underlie Player/Stage, our open source project for rapid development of robot control systems. One product of this project is the Player Abstract Device Interface (PADI) specification, which defines a set of interfaces that capture the functionality of logically similar sensors and actuators. This specification is the central abstraction that enables Player-based controllers to run unchanged on a variety of real and simulated devices. We propose that PADI could be a starting point for development of a standard platform for robot interfacing, independent of Player, to enable code portability and re-use, while still providing access to the unique capabilities of individual devices.

Outdoor Mapping and Navigation Using Stereo Vision

We consider the problem of autonomous navigation in an unstructured outdoor environment. The goal is for a small outdoor robot to come into a new area, learn about and map its environment, and move to a given goal at modest speeds (1 m/s). This problem is especially difficult in outdoor, off-road environments, where tall grass, shadows, deadfall, and other obstacles predominate. Not surprisingly, the biggest challenge is acquiring and using a reliable map of the new area. Although work in outdoor navigation has preferentially used laser rangefinders [14,2,6], we use stereo vision as the main sensor. Vision sensors allow us to use more distant objects as landmarks for navigation, and to learn and use color and texture models of the environment, in looking further ahead than is possible with range sensors alone.

Visibility-based Pursuit-evasion with Limited Field of View

We study the visibility-based pursuit-evasion problem, in which one or more searchers must move through a given environment so as to guarantee detection of any and all evaders, which can move arbitrarily fast. Our goal is to develop techniques for coordinating teams of robots to execute this task in application domains such as clearing a building, for reasons of security or safety. To this end, we introduce a new class of searcher, the φ-searcher, which can be readily instantiated as a physical mobile robot. We present a detailed analysis of the pursuit-evasion problem using φ-searchers. We present the first complete search algorithm for a single φ-searcher, show how this algorithm can be extended to handle multiple searchers, and give examples of computed trajectories.

Pusher-watcher: an approach to fault-tolerant tightly-coupled robot coordination

We present a distributed planar object manipulation algorithm inspired by human behavior. The system, which we call pusher-watcher, enables the cooperative manipulation of large objects by teams of autonomous mobile robots. The robots are not equipped with gripping devices, but instead move objects by pushing against them. The pusher robots have no global positioning information, and cannot see over the object; thus a watcher robot has the responsibility for leading the team (and object) to the goal, which only it can perceive. The system is entirely distributed, with each robot under local control. Through the use of MURDOCH, an auction-based resource-centric general purpose task-allocation framework, roles in the team are automatically assigned in an efficient manner. Further, robot failures are easily tolerated and, when possible, automatically recovered. We present results and analysis from a battery of experiments with pusher-watcher implemented on a group of Pioneer 2 mobile robots.

Principled Communication for Dynamic Multi-robot Task Allocation

In the pursuit of an efficient cooperative multi-robot system, the researcher must eventually answer the question “how should robots communicate?”; a natural way to attack this question is to decompose it into three simpler corollaries: “what should robots communicate?”, “when should they communicate?” and “with whom should they communicate?”. In this paper, we propose answers to these questions in the form of a general framework for inter-robot communication and, more specifically, advocate its use in dynamic task allocation for teams of cooperative mobile robots. We base our communication model on publish/subscribe messaging and validate our system by using it in a tightly-coupled multi-robot manipulaion task and a loosely-coupled long-term experiment involving many robots concurrently executing different tasks.

Murdoch: publish/subscribe task allocation for heterogeneous agents

Introduction In this paper, we describe a novel approach to the problem of dynamic task allocation among groups of heterogeneous agents. Specifically , we advocate the use of publish/subscribe messaging, a well-researched ((S 98)) and commercially proven ((TIB97)) message brokering paradigm that is readily applicable to distributed control. We present MURDOCH, an implemented publish-subscribe system, and explain how it can facilitate multi-robot coordination. Publish/Subscribe Messaging At the heart of MURDOCH is an implementation of publish/subscribe messaging, which in turn depends on subject-based addressing. Subject-based addressing is an addressing scheme in which individual messages are addressed by content rather than destination. Publish/subscribe messaging is a messaging paradigm that uses subject-based addressing to divide a network into a loosely-coupled association of anonymous data producers and consumers. A data producer simply tags a message with a subject (or set of subjects) and “publishes” it onto the network; any data consumers who have “subscribed” to that subject (or set of subjects) will automatically receive the message. The goal of publish/subscribe messaging is to enable a loosely-coupled distributed system in which the data producers have no knowledge of the data consumers and vice versa.

Parallel Stochastic Hill- Climbing with Small Teams

We address the basic problem of coordinating the actions of multiple robots that are working toward a common goal. This kind of problem is NP-hard, because in order to coordinate a system of n robots, it is in principle necessary to generate and evaluate a number of actions or plans that is exponential in n (assuming P ≠ NP). However, we suggest that many instances of coordination problems, despite the NP-hardness of the overall class of problems, do not in practice require exponential computation in order to arrive at good solutions. In such problems, it is not necessary to consider all possible actions of the n robots; instead an algorithm may restrict its attention to interactions within small teams, and still produce high-quality solutions.