Model identification and model analysis in robot training

Robot training is a fast and efficient method of obtaining robot control code. Many current machine learning paradigms used for this purpose, however, result in opaque models that are difficult, if not impossible to analyse, which is an impediment in safety-critical applications or application scenarios where humans and robots occupy the same workspace. In experiments with a Magellan Pro mobile robot we demonstrate that it is possible to obtain transparent models of sensor-motor couplings that are amenable to subsequent analysis, and how such analysis can be used to refine and tune the models post hoc

Robot training using system identification

This paper focuses on developing a formal, theory-based design methodology to generate transparent robot control programs using mathematical functions. The research finds its theoretical roots in robot training and system identification techniques such as Armax (Auto-Regressive Moving Average models with eXogenous inputs) and Narmax (Non-linear Armax). These techniques produce linear and non-linear polynomial functions that model the relationship between a robot’s sensor perception and motor response. The main benefits of the proposed design methodology, compared to the traditional robot programming techniques are: (i) It is a fast and efficient way of generating robot control code, (ii) The generated robot control programs are transparent mathematical functions that can be used to form hypotheses and theoretical analyses of robot behaviour, and (iii) It requires very little explicit knowledge of robot programming where end-users/programmers who do not have any specialised robot programming skills can nevertheless generate task-achieving sensor-motor couplings. The nature of this research is concerned with obtaining sensor-motor couplings, be it through human demonstration via the robot, direct human demonstration, or other means. The viability of our methodology has been demonstrated by teaching various mobile robots different sensor-motor tasks such as wall following, corridor passing, door traversal and route learning

Environmental Hazard Analysis - a Variant of Preliminary Hazard Analysis for Autonomous Mobile Robots

© 2014, Springer Science+Business Media Dordrecht. Robot manufacturers will be required to demonstrate objectively that all reasonably foreseeable hazards have been identified in any robotic product design that is to be marketed commercially. This is problematic for autonomous mobile robots because conventional methods, which have been developed for automatic systems do not assist safety analysts in identifying non-mission interactions with environmental features that are not directly associated with the robot’s design mission, and which may comprise the majority of the required tasks of autonomous robots. In this paper we develop a new variant of preliminary hazard analysis that is explicitly aimed at identifying non-mission interactions by means of new sets of guidewords not normally found in existing variants. We develop the required features of the method and describe its application to several small trials conducted at Bristol Robotics Laboratory in the 2011–2012 period

Robotic manipulators for single access surgery

This thesis explores the development of cooperative robotic manipulators for enhancing surgical precision and patient outcomes in single-access surgery and, specifically, Transanal Endoscopic Microsurgery (TEM). During these procedures, surgeons manipulate a heavy set of instruments via a mechanical clamp inserted in the patient’s body through a surgical port, resulting in imprecise movements, increased patient risks, and increased operating time. Therefore, an articulated robotic manipulator with passive joints is initially introduced, featuring built-in position and force sensors in each joint and electronic joint brakes for instant lock/release capability. The articulated manipulator concept is further improved with motorised joints, evolving into an active tool holder. The joints allow the incorporation of advanced robotic capabilities such as ultra-lightweight gravity compensation and hands-on kinematic reconfiguration, which can optimise the placement of the tool holder in the operating theatre. Due to the enhanced sensing capabilities, the application of the active robotic manipulator was further explored in conjunction with advanced image guidance approaches such as endomicroscopy. Recent advances in probe-based optical imaging such as confocal endomicroscopy is making inroads in clinical uses. However, the challenging manipulation of imaging probes hinders their practical adoption. Therefore, a combination of the fully cooperative robotic manipulator with a high-speed scanning endomicroscopy instrument is presented, simplifying the incorporation of optical biopsy techniques in routine surgical workflows. Finally, another embodiment of a cooperative robotic manipulator is presented as an input interface to control a highly-articulated robotic instrument for TEM. This master-slave interface alleviates the drawbacks of traditional master-slave devices, e.g., using clutching mechanics to compensate for the mismatch between slave and master workspaces, and the lack of intuitive manipulation feedback, e.g. joint limits, to the user. To address those drawbacks a joint-space robotic manipulator is proposed emulating the kinematic structure of the flexible robotic instrument under control.Open Acces