(Georgia Institute of Technology, 1999)
Ali, Khaled Subhi; Arkin, Ronald C.; Cervantes-Pérez, Francisco; Weitzenfeld, Alfredo
Formal models of animal sensorimotor behavior can provide effective methods
for generating robotic intelligence. In this article we describe how schema-theoretic
models of the praying mantis derived from behavioral and neuroscientific data can
be implemented on a hexapod robot equipped with a real-time color vision system.
This implementation incorporates a wide range of behaviors, including obstacle
avoidance, prey acquisition, predator avoidance, mating, and chantlitaxia behaviors
that can provide guidance to neuroscientists, ethologists, and roboticists alike. The
goals of this study are threefold: to provide an understanding and means by which
fielded robotic systems are not competing with other agents that are more effective
at their designated task; to permit them to be successful competitors within the
ecological system and capable of displacing less efficient agents; and that they are
ecologically sensitive so that agent-environment dynamics are well-modeled and as
predictable as possible whenever new robotic technology is introduced.
(Georgia Institute of Technology, 1998)
Arkin, Ronald C.; Cervantes-Pérez, Francisco; Corbacho, Fernando; Olivares, Roberto; Weitzenfeld, Alfredo
As autonomous robots become more complex in their behavior, more sophisticated software
architectures are required to support the ever more sophisticated robotics software. These
software architectures must support complex behaviors involving adaptation and learning,
implemented, in particular, by neural networks. We present in this paper a neural based schema
[2] software architecture for the development and execution of autonomous robots in both
simulated and real worlds. This architecture has been developed in the context of adaptive
robotic agents, ecological robots [6], cooperating and competing with each other in adapting to
their environment. The architecture is the result of integrating a number of development and
execution systems: NSL, a neural simulation language; ASL, an abstract schema language; and
MissionLab, a schema-based mission-oriented simulation and robot system. This work
contributes to modeling in Brain Theory (BT) and Cognitive Psychology, with applications in
Distributed Artificial Intelligence (DAI), Autonomous Agents and Robotics.
(Georgia Institute of Technology, 1998)
Arkin, Ronald C.; Cervantes-Pérez, Francisco; Peniche, José Francisco; Weitzenfeld, Alfredo
Autonomous biological systems are very complex in their nature. Their study, through both experimentation and computation, provides a means to understand the underlying mechanisms in living systems while inspiring the development of technological applications. Experimentation, consisting of data gathering, generates predictions to be validated by experimentation on artificial systems. Computational models provide the understanding for the underlying dynamics, and serve as basis for simulation and further experimentation. The work presented here involves analyzing how predictive models can be generated from biological systems and then be used to drive robotic experiments; and conversely, how can results from robotic experiments drive additional neuroethological data gathering. This process requires a variety of visualization techniques in modeling and simulation of increasingly complex systems.
(Georgia Institute of Technology, 1997)
Arkin, Ronald C.; Cervantes-Pérez, Francisco; Weitzenfeld, Alfredo
The goals of this joint U.S.-Mexico research project are threefold: to provide an understanding and means by which fielded robotic systems are not competing with other agents that are more effective at their designated task; to permit them to be successful competitors within the ecological system and capable of displacing less efficient agents; and that they are ecologically sensitive so that agent environment dynamics are well-modeled and as predictable as possible whenever new robotic technology is introduced. Initial studies on neuroscientifically derived schema models of the praying mantis and frog are reported that have led to simulation studies and eventual robotic implementations that can provide guidance to neuroscientists, ethologists, and roboticists alike.