Carnegie Mellon Robotics Institute
doctoral dissertation, tech. report CMU-RI-TR-97-01, Robotics Institute, Carnegie Mellon University, January, 1997
|In unstructured, unknown, and dynamic environments, planning systems cannot generate a plan a priori that can be expected to perform reasonably in the face of such uncertainty, nor can they anticipate all contingencies that may arise; instead, decision-making must be based on current information and state at all times, proceeding in a data-driven manner, rather than attempting to impose unrealizable plans in a top-down fashion. In addition, the dynamics of the vehicle itself often play an important role in determining which actions may be achieved and which actions are to be avoided. For complex domains such as mobile robot navigation, there also exists the need to combine information from several different sources to be used to perform diverse tasks. A system architecture should be able to accommodate and integrate subsystems that have been developed independently, therefore it must impose minimal restrictions on the nature of the data, representations, and algorithms used by these subsystems designed to achieve their respective tasks. Also, sensors and the functions that process their data each operate at different rates, so they must be allowed to operate asynchronously to maximize the throughput and thus the responsiveness of the system.
The Distributed Architecture for Mobile Navigation (DAMN) is a planning and control architecture in which a collection of independently operating modules collectively determine a robot's actions. DAMN consists of a group of distributed behaviors communicating with a centralized arbiter, either by sending votes in favor of actions that satisfy its objectives, or by indicating the utility of various possible world states. The arbiter is then responsible for combining the behaviors' votes and generating actions which reflects their objectives and priorities. The use of distributed shared control allows multiple levels of planning to be used in decision-making without the need for an hierarchical structure, and the distributed, asynchronous nature of the architecture allows multiple goals and constraints to be fulfilled simultaneously. Thus, DAMN provides coherent, rational, goal-directed behavior while preserving real-time responsiveness to its immediate physical environment. DAMN also provides a framework for developing and integrating independent decision-making modules communicating with such arbiters, thus facilitating their development and leading to evolutionary creation of robust systems of incrementally greater capabilities.
DAMN has been used to combine various systems of differing capabilities on several mobile robots, and has also been used for active sensor control. Various subsystems developed at Carnegie Mellon University and elsewhere have been integrated within this architecture, creating systems that perform road following, cross-country navigation, map-based route following, and teleoperation while avoiding obstacles and meeting mission objectives.
Grant ID: BCS-9120655
Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): NavLab
Associated Project(s): Distributed Architecture for Mobile Navigation
|Julio Rosenblatt, "DAMN: A Distributed Architecture for Mobile Navigation," doctoral dissertation, tech. report CMU-RI-TR-97-01, Robotics Institute, Carnegie Mellon University, January, 1997|
author = "Julio Rosenblatt",
title = "DAMN: A Distributed Architecture for Mobile Navigation",
booktitle = "",
school = "Robotics Institute, Carnegie Mellon University",
month = "January",
year = "1997",
address= "Pittsburgh, PA",
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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