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Distributed Architecture for Mobile Navigation (DAMN)
This project is no longer active.

Head: Julio Rosenblatt
Contact: Chuck Thorpe (thorpe@qatar.cmu.edu)

Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213

Associated center: VASC
Associated lab/group: NavLab


Jump to: Project Description | Personnel | Sub-projects | Publications

Project Description

The Distributed Architecture for Mobile Navigation, or DAMN, consists of a group of distributed behaviors communicating with a centralized command arbiter, sending votes in favor of actions that satisfy its objectives and against those actions which do not. The arbiter is then responsible for combining the behaviors' votes and generating actions which reflects their objectives and priorities, thus providing the responsiveness and robustness of behavior-based systems without sacrificing the coherence and rationality of centralized architectures.

Various voting schemes have been implemented that allow for the simultaneous satisfaction of multiple goals and objectives in a distributed system. One such voting scheme is a fuzzy logic type of approach where behaviors express their preferences among a set of possible actions; the arbiter sums these votes and selects the maximum. The second is a schema-based type of approach where behaviors instead indicate the utility of possible world states; the arbiter then maintains a local utility map and evaluates possible actions within it.

DAMN has been used to create various systems for mobile robot navigation and active sensor control. Diverse subsystems have been integrated within this architecture to create systems that, for example, perform road following, cross-country navigation, map-based route following, and teleoperation while avoiding obstacles and meeting mission objectives.

Past members

Name Title Email Address
Julio's personal homepage Julio Rosenblatt PhD Student, RI
Chuck Thorpe Dean, Qatar Campus thorpe@qatar.cmu.edu

Past Sub-projects

A Reactive System for Off-Road Autonomous Driving - We have developed an integrated obstacle avoidance system for on-road driving for avoiding discrete obstacles, or for off-road driving for avoiding untraversable regions of terrain.
 

Publications

Note: This list may not be comprehensive. It contains only those publications in the RI publications database. Entries are listed in reverse chronological order.


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