An integrated diagnostic architecture for autonomous robots

Abstract unavailable please refer to PD

Formalizing the Execution Context of Behavior Trees for Runtime Verification of Deliberative Policies

In this paper, we enable automated property verification of deliberative components in robot control architectures. We focus on formalizing the execution context of Behavior Trees (BTs) to provide a scalable, yet formally grounded, methodology to enable runtime verification and prevent unexpected robot behaviors. To this end, we consider a message-passing model that accommodates both synchronous and asynchronous composition of parallel components, in which BTs and other components execute and interact according to the communication patterns commonly adopted in robotic software architectures. We introduce a formal property specification language to encode requirements and build runtime monitors. We performed a set of experiments, both on simulations and on the real robot, demonstrating the feasibility of our approach in a realistic application and its integration in a typical robot software architecture. We also provide an OS-level virtualization environment to reproduce the experiments in the simulated scenario

Autosub Long Range 1500: A continuous 2000 km field trial

Long Range Autonomous Underwater Vehicles (LRAUVs) offer the potential to monitor the ocean at higher spatial and temporal resolutions compared to conventional ship-based techniques. The multi-week to multi-month endurance of LRAUVs enables them to operate independently of a support vessel, creating novel opportunities for ocean observation. The National Oceanography Centre’s Autosub Long Range is one of a small number of vehicles designed for a multi-month endurance. The latest iteration, Autosub Long Range 1500 (ALR1500), is a 1500 m depth-rated LRAUV developed for ocean science in coastal and shelf seas or in the epipelagic and meteorologic regions of the ocean. This paper presents the design of the ALR1500 and results from a five week continuous deployment from Plymouth, UK, to the continental shelf break and back again, a distance of approximately 2000km which consumed half of the installed energy. The LRAUV was unaccompanied throughout the mission and operated continuously beyond visual line of sight

Behaviour-driven motion synthesis

Heightened demand for alternatives to human exposure to strenuous and repetitive labour, as well as to hazardous environments, has led to an increased interest in real-world deployment of robotic agents. Targeted applications require robots to be adept at synthesising complex motions rapidly across a wide range of tasks and environments. To this end, this thesis proposes leveraging abstractions of the problem at hand to ease and speed up the solving. We formalise abstractions to hint relevant robotic behaviour to a family of planning problems, and integrate them tightly into the motion synthesis process to make real-world deployment in complex environments practical. We investigate three principal challenges of this proposition. Firstly, we argue that behavioural samples in form of trajectories are of particular interest to guide robotic motion synthesis. We formalise a framework with behavioural semantic annotation that enables the storage and bootstrap of sets of problem-relevant trajectories. Secondly, in the core of this thesis, we study strategies to exploit behavioural samples in task instantiations that differ significantly from those stored in the framework. We present two novel strategies to efficiently leverage offline-computed problem behavioural samples: (i) online modulation based on geometry-tuned potential fields, and (ii) experience-guided exploration based on trajectory segmentation and malleability. Thirdly, we demonstrate that behavioural hints can be extracted on-the-fly to tackle highlyconstrained, ever-changing complex problems, from which there is no prior knowledge. We propose a multi-layer planner that first solves a simplified version of the problem at hand, to then inform the search for a solution in the constrained space. Our contributions on efficient motion synthesis via behaviour guidance augment the robots’ capabilities to deal with more complex planning problems, and do so more effectively than related approaches in the literature by computing better quality paths in lower response time. We demonstrate our contributions, in both laboratory experiments and field trials, on a spectrum of planning problems and robotic platforms ranging from high-dimensional humanoids and robotic arms with a focus on autonomous manipulation in resembling environments, to high-dimensional kinematic motion planning with a focus on autonomous safe navigation in unknown environments. While this thesis was motivated by challenges on motion synthesis, we have explored the applicability of our findings on disparate robotic fields, such as grasp and task planning. We have made some of our contributions open-source hoping they will be of use to the robotics community at large.The CDT in Robotics and Autonomous Systems at Heriot-Watt University and The University of EdinburghThe ORCA Hub EPSRC project (EP/R026173/1)The Scottish Informatics and Computer Science Alliance (SICSA

The augmented reality framework : an approach to the rapid creation of mixed reality environments and testing scenarios

Debugging errors during real-world testing of remote platforms can be time consuming and expensive when the remote environment is inaccessible and hazardous such as deep-sea. Pre-real world testing facilities, such as Hardware-In-the-Loop (HIL), are often not available due to the time and expense necessary to create them. Testing facilities tend to be monolithic in structure and thus inflexible making complete redesign necessary for slightly different uses. Redesign is simpler in the short term than creating the required architecture for a generic facility. This leads to expensive facilities, due to reinvention of the wheel, or worse, no testing facilities. Without adequate pre-real world testing, integration errors can go undetected until real world testing where they are more costly to diagnose and rectify, e.g. especially when developing Unmanned Underwater Vehicles (UUVs). This thesis introduces a novel framework, the Augmented Reality Framework (ARF), for rapid construction of virtual environments for Augmented Reality tasks such as Pure Simulation, HIL, Hybrid Simulation and real world testing. ARF’s architecture is based on JavaBeans and is therefore inherently generic, flexible and extendable. The aim is to increase the performance of constructing, reconfiguring and extending virtual environments, and consequently enable more mature and stable systems to be developed in less time due to previously undetectable faults being diagnosed earlier in the pre-real-world testing phase. This is only achievable if test harnesses can be created quickly and easily, which in turn allows the developer to visualise more system feedback making faults easier to spot. Early fault detection and less wasted real world testing leads to a more mature, stable and less expensive system. ARF provides guidance on how to connect and configure user made components, allowing for rapid prototyping and complex virtual environments to be created quickly and easily. In essence, ARF tries to provide intuitive construction guidance which is similar in nature to LEGOR pieces which can be so easily connected to form useful configurations. ARF is demonstrated through case studies which show the flexibility and applicability of ARF to testing techniques such as HIL for UUVs. In addition, an informal study was carried out to asses the performance increases attributable to ARF’s core concepts. In comparison to classical programming methods ARF’s average performance increase was close to 200%. The study showed that ARF was incredibly intuitive since the test subjects were novices in ARF but experts in programming. ARF provides key contributions in the field of HIL testing of remote systems by providing more accessible facilities that allow new or modified testing scenarios to be created where it might not have been feasible to do so before. In turn this leads to early detection of faults which in some cases would not have ever been detected before

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties