Towards an Ethical Robot: Internal Models, Consequences and Ethical Action Selection
If robots are to be trusted, especially when interacting with humans, then they will need to be more than just safe. This paper explores the potential of robots capable of modelling and therefore predicting the consequences of both their own actions, and the actions of other dynamic actors in their environment. We show that with the addition of an ‘ethical’ action selection mechanism a robot can sometimes choose actions that compromise its own safety in order to prevent a second robot from coming to harm. An implementation with e-puck mobile robots provides a proof of principle by showing that a simple robot can, in real time, model and act upon the consequences of both its own and another robot’s actions. We argue that this work moves us towards robots that are ethical, as well as safe.
KeywordsHuman-Robot Interaction Safety Internal Model Machine Ethics
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- 1.Asimov, I.: I, ROBOT. Gnome Press (1950)Google Scholar
- 3.Braitenberg, V.: Vehicles: Experiments in synthetic psychology. MIT Press (1984)Google Scholar
- 4.Holland, J.: Complex Adaptive Systems. Daedalus (1992)Google Scholar
- 5.Holland, O. (ed.): Machine Consciousness. Imprint Academic (2003)Google Scholar
- 7.Liu, W., Winfield, A.F.T.: Open-hardware e-puck Linux extension board for experimental swarm robotics research. Microprocessors and Microsystems 35(1) (2011)Google Scholar
- 9.Michel, O.: Webots: Professional mobile robot simulation. International Journal of Advanced Robotic Systems 1(1), 39–42 (2004)Google Scholar
- 10.Mondada, F., Bonani, M., Raemy, X., Pugh, J., Cianci, C., Klaptocz, A., Magnenat, S., Zufferey, J.C., Floreano, D., Martinoli, A.: The e-puck, a robot designed for education in engineering. In: Proc. 9th Conference on Autonomous Robot Systems and Competitions, pp. 59–65 (2009)Google Scholar
- 11.O’Dowd, P.J., Winfield, A.F.T., Studley, M.: The distributed co-evolution of an embodied simulator and controller for swarm robot behaviours. In: Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), pp. 4995–5000 (2011)Google Scholar
- 12.Stepney, S., Welch, P., Andrews, P. (eds.): CoSMoS 2011: Proc. 2011 Workshop on Complex Systems Modelling and Simulation. Luniver Press (2011)Google Scholar
- 14.Vaughan, R.T., Gerkey, B.P.: Really reused robot code from the player/stage project. In: Brugali, D. (ed.) Software Engineering for Experimental Robotics, pp. 267–289. Springer (2007)Google Scholar
- 15.Vaughan, R.T., Zuluaga, M.: Use your illusion: Sensorimotor self-simulation allows complex agents to plan with incomplete self-knowledge. In: Proc. International Conference on Simulation of Adaptive Behaviour (SAB), pp. 298–309 (2006)Google Scholar
- 16.Wallach, W., Allen, C.: Moral Machines: Teaching Robots Right from Wrong. Oxford University Press, Oxford (2009)Google Scholar