Wei-Min Shen

Adopt: asynchronous distributed constraint optimization with quality guarantees

The Distributed Constraint Optimization Problem (DCOP) is a promising approach for modeling distributed reasoning tasks that arise in multiagent systems. Unfortunately, existing methods for DCOP are not able to provide theoretical guarantees on global solution quality while allowing agents to operate asynchronously. We show how this failure can be remedied by allowing agents to make local decisions based on conservative cost estimates rather than relying on global certainty as previous approaches have done. This novel approach results in a polynomial-space algorithm for DCOP named Adopt that is guaranteed to find the globally optimal solution while allowing agents to execute asynchronously and in parallel. Detailed experimental results show that on benchmark problems Adopt obtains speedups of several orders of magnitude over other approaches. Adopt can also perform bounded-error approximation-it has the ability to quickly find approximate solutions and, unlike heuristic search methods, still maintain a theoretical guarantee on solution quality.

Modular Self-Reconfigurable Robot Systems [Grand Challenges of Robotics]

The field of modular self-reconfigurable robotic systems addresses the design, fabrication, motion planning, and control of autonomous kinematic machines with variable morphology. Modular self-reconfigurable systems have the promise of making significant technological advances to the field of robotics in general. Their promise of high versatility, high value, and high robustness may lead to a radical change in automation. Currently, a number of researchers have been addressing many of the challenges. While some progress has been made, it is clear that many challenges still exist. By illustrating several of the outstanding issues as grand challenges that have been collaboratively written by a large number of researchers in this field, this article has shown several of the key directions for the future of this growing field

Query reformulation for dynamic information integration

The standard approach to integrating heterogeneous information sources is to build a global schema that relates all of the information in the different sources, and to pose queries directly against it. The problem is that schema integration is usually difficult, and as soon as any of the information sources change or a new source is added, the process may have to be repeated.The SIMS system uses an alternative approach. A domain model of the application domain is created, establishing a fixed vocabulary for describing data sets in the domain. Using this language, each available information source is described. Queries to SIMS against the collection of available information sources are posed using terms from the domain model, and reformulation operators are employed to dynamically select an appropriate set of information sources and to determine how to integrate the available information to satisfy a query. This approach results in a system that is more flexible than existing ones, more easily scalable, and able to respond dynamically to newly available or unexpectedly missing information sources.This paper describes the query reformulation process in SIMS and the operators used in it. We provide precise definitions of the reformulation operators and explain the rationale behind choosing the specific ones SIMS uses. We have demonstrated the feasibility and effectiveness of this approach by applying SIMS in the domains of transportation planning and medical trauma care.

Hormone-inspired adaptive communication and distributed control for CONRO self-reconfigurable robots

Presents a biologically inspired approach to two basic problems in modular self-reconfigurable robots: adaptive communication in self-reconfigurable and dynamic networks, and distributed collaboration between the physically coupled modules to accomplish global effects such as locomotion and reconfiguration. Inspired by the biological concept of hormone, the paper develops the adaptive communication (AC) protocol that enables modules continuously to discover changes in their local topology, and the adaptive distributed control (ADC) protocol that allows modules to use hormone-like messages in collaborating their actions to accomplish locomotion and self-reconfiguration. These protocols are implemented and evaluated, and experiments in the CONRO self-reconfigurable robot and in a Newtonian simulation environment have shown that the protocols are robust and scaleable when configurations change dynamically and unexpectedly, and they can support online reconfiguration, module-level behavior shifting, and locomotion. The paper also discusses the implication of the hormone-inspired approach for distributed multiple robots and self-reconfigurable systems in general.

Resource integration using a large knowledge base in Carnot

A method for integrating separately developed information resources that overcomes incompatibilities in syntax and semantics and permits the resources to be accessed and modified coherently is described. The method provides logical connectivity among the information resources via a semantic service layer that automates the maintenance of data integrity and provides an approximation of global data integration across systems. This layer is a fundamental part of the Carnot architecture, which provides tools for interoperability across global enterprises.<<ETX>>

SUPERBOT: A Deployable, Multi-Functional, and Modular Self-Reconfigurable Robotic System

Self-reconfigurable robots are modular robots that can autonomously change their shape and size to meet specific operational demands. Recently, there has been a great interest in using self-reconfigurable robots in applications such as reconnaissance, rescue missions, and space applications. Designing and controlling self-reconfigurable robots is a difficult task. Hence, the research has primarily been focused on developing systems that can function in a controlled environment. This paper presents a novel self-reconfigurable robotic system called SuperBot, which addresses the challenges of building and controlling deployable self-reconfigurable robots. Six prototype modules have been built and preliminary experimental results demonstrate that SuperBot is a flexible and powerful system that can be used in challenging real-world applications

An asynchronous complete method for distributed constraint optimization

We present a new polynomial-space algorithm, called Adopt, for distributed constraint optimization (DCOP). DCOP is able to model a large class of collaboration problems in multi agent systems where a solution within given quality parameters must be found. Existing methods for DCOP are not able to provide theoretical guarantees on global solution quality while operating both efficiently and asynchronously. Adopt is guaranteed to find an optimal solution, or a solution within a user-specified distance from the optimal, while allowing agents to execute asynchronously and in parallel. Adopt obtains these properties via a distributed search algorithm with several novel characteristics including the ability for each agent to make local decisions based on currently available information and without necessarily having global certainty. Theoretical analysis shows that Adopt provides provable quality guarantees, while experimental results show that Adopt is significantly more efficient than synchronous methods. The speedups are shown to be partly due to the novel search strategy employed and partly due to the asynchrony of the algorithm.

CONRO: Towards Deployable Robots with Inter-Robots Metamorphic Capabilities

Metamorphic robots are modular robots that can reconfigure their shape. Such capability is desirable in tasks such as earthquake search and rescue and battlefield surveillance and scouting, where robots must go through unexpected situations and obstacles and perform tasks that are difficult for fixed-shape robots. The capabilities of the robots are determined by the design specification of their modules. In this paper, we present the design specification of a CONRO module, a small, self-sufficient and relatively homogeneous module that can be connected to other modules to form complex robots. These robots have not only the capability of changing their shape (intra-robot metamorphing) but also can split into smaller robots or merge with other robots to create a single larger robot (inter-robot metamorphing), i.e., CONRO robots can alter their shape and their size. Thus, heterogeneous robot teams can be built with homogeneous components. Furthermore, the CONRO robots can separate the reconfiguration stage from the locomotion stage, allowing the selection of configuration-dependent gaits. The locomotion and automatic inter-module docking capabilities of such robots were tested using tethered prototypes that can be reconfigured manually. We conclude the paper discussing the future work needed to fully realize the construction of these robots.

A Dynamic Distributed Constraint Satisfaction Approach to Resource Allocation

In distributed resource allocation a set of agents must assign their resources to a set of tasks. This problem arises in many real-world domains such as disaster rescue, hospital scheduling and the domain described in this paper: distributed sensor networks. Despite the variety of approaches proposed for distributed resource allocation, a systematic formalization of the problem and a general solution strategy are missing. This paper takes a step towards this goal by proposing a formalization of distributed resource allocation that represents both dynamic and distributed aspects of the problem and a general solution strategy that uses distributed constraint satisfaction techniques. This paper defines the notion of Dynamic Distributed Constraint Satisfaction Problem (DyDCSP) and proposes two generalized mappings from distributed resource allocation to DyDCSP, each proven to correctly perform resource allocation problems of specific difficulty and this theoretical result is verified in practice by an implementation on a real-world distributed sensor network.

Hormone-controlled metamorphic robots

Metamorphic robots with shape-changing capabilities provide a powerful and flexible approach to complex tasks in unstructured environments. However, due to their dynamic topology and decentralized configuration, metamorphic robots demand control mechanisms that go beyond those used by conventional robots. This paper builds on our previous results of hormone-based control, and develops a novel distributed control algorithm called CELL that can select, synchronize, and execute gaits and other reconfiguration actions without assuming any global configuration knowledge. This algorithm is flexible enough to deal with changes of configuration, and can resolve conflicts between locally selected actions and manage multiple active hormones for producing coherent global effects.