Written evidence submitted to the UK Parliamentary Select Committee on Science and Technology Inquiry on Robotics and Artificial Intelligence

This paper was submitted in response to question 4 of the Parliamentary Science and Technology Committee Inquiry on Robotics and Artificial Intelligence* on: 'The social, legal and ethical issues raised by developments in robotics and artificial intelligence technologies, and how they should be addressed'. The paper was drafted at the request of EPSRC and the UK Robotics and Autonomous Systems (RAS) Network, and an abridged version is incorporated into the UK RAS response to the inquiry.*http://www.parliament.uk/business/committees/committees-a-z/commons-select/science-and-technology-committee/inquiries/parliament-2015/robotics-and-artificial-intelligence-inquiry-15-16

Towards Verifiably Ethical Robot Behaviour

Ensuring that autonomous systems work ethically is both complex and difficult. However, the idea of having an additional `governor' that assesses options the system has, and prunes them to select the most ethical choices is well understood. Recent work has produced such a governor consisting of a `consequence engine' that assesses the likely future outcomes of actions then applies a Safety/Ethical logic to select actions. Although this is appealing, it is impossible to be certain that the most ethical options are actually taken. In this paper we extend and apply a well-known agent verification approach to our consequence engine, allowing us to verify the correctness of its ethical decision-making.Comment: Presented at the 1st International Workshop on AI and Ethics, Sunday 25th January 2015, Hill Country A, Hyatt Regency Austin. Will appear in the workshop proceedings published by AAA

Editorial: Special issue on ground robots operating in dynamic, unstructured and large-scale outdoor environments

Real-world outdoor applications of ground robots have, to date, been limited primarily to remote inspection of suspected explosive devices and, with less success, to the broader domain of remote survey and inspection in hazardous environments. Such robots have almost exclusively been tele-operated. Also notable as examples of outdoor ground robots are the planetary rovers, currently deployed with great success on the surface of Mars. But with the rapid development of autonomous (driverless) cars, and the emergence of robotic vehicles in agriculture, it is likely that there will be significant growth in both the numbers and scope of commercial ground robots in outdoor environments in the near future.For this special issue we called for papers that present land robot systems deployed in the field in similar realistic challenges. We sought papers that focus on any aspect of robotic systems, from vehicle design to the overall system architecture and control, via terrain mapping, localization, mission planning and execution – with an emphasis on systems that fulfil a specific real world task. We specified that robot or system innovations must be supported by extensive field results. Also that field tests must be under realistic and challenging conditions with respect to the terrain type, the scenario to be achieved, and/or the conditions within which the scenarios must be achieved

An architecture for ethical robots inspired by the simulation theory of cognition

The expanding ability of robots to take unsupervised decisions renders it imperative that mechanisms are in place to guarantee the safety of their behaviour. Moreover, intelligent autonomous robots should be more than safe; arguably they should also be explicitly ethical. In this paper, we put forward a method for implementing ethical behaviour in robots inspired by the simulation theory of cognition. In contrast to existing frameworks for robot ethics, our approach does not rely on the verification of logic statements. Rather, it utilises internal simulations which allow the robot to simulate actions and predict their consequences. Therefore, our method is a form of robotic imagery. To demonstrate the proposed architecture, we implement a version of this architecture on a humanoid NAO robot so that it behaves according to Asimov's laws of robotics. In a series of four experiments, using a second NAO robot as a proxy for the human, we demonstrate that the Ethical Layer enables the robot to prevent the human from coming to harm in simple test scenarios

Open-hardware e-puck Linux extension board for experimental swarm robotics research

In this paper we describe the implementation of a Linux extension board for the e-puck educational mobile robot, designed to enhance the computation, memory and networking performance of the robot at very low cost. The extension board is based on a 32-bit ARM9 microprocessor and provides wireless network support. The ARM9 extension board runs in parallel with the dsPIC microprocessor on the e-puck motherboard with communication between the two via an SPI bus. The extension board is designed to handle computationally intensive image processing, wireless communication and high-level intelligent robot control algorithms, while the dsPIC handles low-level sensor interfacing, data processing and motor control. The extension board runs an embedded Linux operating system, along with a Debian-based port of the root file system stored in a Micro SD card. The extended e-puck robot platform requires minimal effort to integrate the well-known open-source robot control framework Player and, when placed within a TCP/IP networked infrastructure, provides a powerful and flexible platform for experimental swarm robotics research. © 2010 Elsevier B.V. All rights reserved

Modeling and optimization of adaptive foraging in swarm robotic systems

Understanding the effect of individual parameters on the collective performance of swarm robotic systems in order to design and optimize individual robot behaviors is a significant challenge. In this paper we present a macroscopic probabilistic model of adaptive collective foraging in a swarm of robots, where each robot in the swarm is capable of adjusting its time threshold parameters following the rules described by Liu et al. 2007. The swarm adapts the ratio of foragers to resters (division of labor) in order to maximize the net swarm energy for a given food density. A probabilistic finite state machine (PFSM) and a number of difference equations are developed to describe collective foraging at a macroscopic level. To model adaptation we introduce the new concepts of the sub-PFSM and private/public time thresholds. The model has been validated extensively with simulation trials, and results show that the model achieves very good accuracy in predicting the group performance of the swarm. Finally, a real-coded genetic algorithm is used to explore the parameter spaces and optimize the parameters of the adaptation algorithm. Although this paper presents a macroscopic probabilistic model for adaptive foraging, we argue that the approach could be applied to any adaptive swarm system in which the heterogeneity of the system is coupled with its time parameters

Run-time detection of faults in autonomous mobile robots based on the comparison of simulated and real robot behaviour

© 2014 IEEE. This paper presents a novel approach to the run-time detection of faults in autonomous mobile robots, based on simulated predictions of real robot behaviour. We show that although simulation can be used to predict real robot behaviour, drift between simulation and reality occurs over time due to the reality gap. This necessitates periodic reinitialisation of the simulation to reduce false positives. Using a simple obstacle avoidance controller afflicted with partial motor failure, we show that selecting the length of this reinitialisation time period is non-trivial, and that there exists a trade-off between minimising drift and the ability to detect the presence of faults