This paper investigates an autonomous control system of a mobile robot based on the immune network theory. The immune network navigates the robot to solve a multiobjective task, namely, garbage collection: the robot must find and collect garbage, while it establishes a trajectory without colliding with obstacles, and return to the base before it runs out of energy. Each network node corresponds to a specific antibody and describes a particular control action for the robot. The antigens are the current state of the robot, read from a set of internal and external sensors. The network dynamics corresponds to the variation of antibody concentration levels, which change according to both mutual interaction of antibody nodes and of antibodies and antigens. It is proposed an evolutionary mechanism to determine the network configuration, that is, the parameters that define those interactions. Simulation results suggest that the proposal presented is very promising. © 2002 IEEE.2 10211026Arkin, R.C., (1998) Behavior-Based Robotics, 355 (357), pp. 123-130. , MIT PressBrooks, R., Intelligence without reason (1991) Proceedings of the IJCAI-91, pp. 569-595Steels, L., Exploiting Analogical representations (1990) Designing Autonomous Agents, pp. 71-88. , ed. P. Maes MIT PressMaes, P., The dynamics of action selection (1989) Proceedings of Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89), pp. 991-997. , Detroit, MIMaes, P., Situated agents can have goals (1990) Robotics and Autonomous Systems, 6, pp. 49-70Grenfenstette, J., Ramsey, C., Schultz, A., Learning sequential decision rules using simulation models and competition (1990) Machine Learning, 5 (4), pp. 355-381Potter, M., Dc Jong, K., Grenfenstette, J., A coevolutionary approach to learning sequential decision rules (1995) Proceedings of the Fifth International Confrrence (JCGA95), , Pittsburgh, PennsylvaniaDe Castro, L.N., (2001) Immune Engineering: Development of Computational Tools Inspired by the Artificial Immune Systems, , (in Portuguese), Ph D Thesis, DCA-FEEC/UNICAMP, Campinas/SP, Brazil, MayJeme, N.K., (1973) The Immune System Scientific American, 229 (1), pp. 52-60Jerne, N.K., Idiotypic networks and other preconceived ideas (1984) Immunological Rev, 79, pp. 5-24Segel, L.A., The immune system as a prototype of autonomous decentralized systems (1997) Proceedings of Conference on Systems. Man and Cybernetics (SMC'97), 1, pp. 375-385. , Orlando, Florida, USAIshiguro, A., Lchikawa, S., Uchikawa, Y., A gait acquisition of six-legged robot using immune networks (1994) Proceedings of International Conference on Intelligent Robotics and Systems (IROS'94), 2, pp. 1034-1041. , Munich, GermanyMitsumoto, N., Fukuda, T., Arai, F., Tadashi, H., Idogaki, T., Self-organizing multiple robotic system (1996) Proceedings of IEEE International Conference on Robotics and Automation, pp. 1614-1619. , Minneapolis, MN AprilIshiguro, A., Kondo, T., Watanabe, Y., Shirai, Y., Uchikawa, H., Immunoid: A robot with a decentralized consensus-making mechanism based on the immune system (1996) ICMAS Workshop on Immunity-Based Systems, pp. 82-92. , Presented at DecemberHolland, J.H., (1975) Adaptation in Natural and Artificial Systems, , University Michigan PressPfeifer, R., Scheier, C., (1999) Understanding Intelligence, 11. , MIT Press Chapter