TY - JOUR
T1 - C4
T2 - A software environment for modeling self-organizing behaviors of autonomous robots and groups
AU - Liu, Jiming
AU - Qin, Hong
N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 1997
Y1 - 1997
N2 - One of the important characteristics of an autonomous robot lies in the capability of self-organizing its own behaviors in order to adapt to an unknown environment.1,2 The goal of this paper is to present an effective means for investigating such a capability, which enables us to graphically build a model of the autonomous robot and dynamically observe the emergence of reactive behaviors as a result of external stimulus controlled behavioral self-organization. In particular, the paper describes an integrated software workbench, called C4 (which stands for Create, Coordinate, Condition, and Co-evolve), for modeling and simulating autonomous robotic systems, e.g., legged and dual-arm ones. The module create enables us to build top-down graphical models of novel mechanisms, followed by primitive motion pattern (e.g., gaits) specification and visualization in the coordinate module. Learning mechanisms, as embedded in module condition further allow us to test how the animated robots acquire new behavioral rules triggerable by external stimuli. Finally, the module co-evolve facilitates the analysis of the distributed intelligence of robot groups, which manifests itself from the behaviors emergent from the interaction among individual robots.
AB - One of the important characteristics of an autonomous robot lies in the capability of self-organizing its own behaviors in order to adapt to an unknown environment.1,2 The goal of this paper is to present an effective means for investigating such a capability, which enables us to graphically build a model of the autonomous robot and dynamically observe the emergence of reactive behaviors as a result of external stimulus controlled behavioral self-organization. In particular, the paper describes an integrated software workbench, called C4 (which stands for Create, Coordinate, Condition, and Co-evolve), for modeling and simulating autonomous robotic systems, e.g., legged and dual-arm ones. The module create enables us to build top-down graphical models of novel mechanisms, followed by primitive motion pattern (e.g., gaits) specification and visualization in the coordinate module. Learning mechanisms, as embedded in module condition further allow us to test how the animated robots acquire new behavioral rules triggerable by external stimuli. Finally, the module co-evolve facilitates the analysis of the distributed intelligence of robot groups, which manifests itself from the behaviors emergent from the interaction among individual robots.
KW - Autonomous robot simulation
KW - Behaviors
KW - Self-organizing
KW - Virtual task environments
UR - http://www.scopus.com/inward/record.url?scp=0030817732&partnerID=8YFLogxK
U2 - 10.1017/S0263574797000106
DO - 10.1017/S0263574797000106
M3 - Journal article
AN - SCOPUS:0030817732
SN - 0263-5747
VL - 15
SP - 85
EP - 98
JO - Robotica
JF - Robotica
IS - 1
ER -