Probabilistic Hybrid Action Models for Predicting Concurrent Percept-driven Robot Behavior

This article develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predicting the behavior generated by modern percept-driven robot plans. PHAMs represent aspects of robot behavior that cannot be represented by most action models used in AI planning: the temporal structure of continuous control processes, their non-deterministic effects, several modes of their interferences, and the achievement of triggering conditions in closed-loop robot plans. The main contributions of this article are: (1) PHAMs, a model of concurrent percept-driven behavior, its formalization, and proofs that the model generates probably, qualitatively accurate predictions; and (2) a resource-efficient inference method for PHAMs based on sampling projections from probabilistic action models and state descriptions. We show how PHAMs can be applied to planning the course of action of an autonomous robot office courier based on analytical and experimental results

Commercial software tools for intelligent autonomous systems

This article identifies some of the commercial software tools that can potentially be examined, or relied upon for their techniques, within new EPSRC projects entitled "Reconfigurable Autonomy" and "Distributed Sensing and Control.." awarded and to be undertaken between Liverpool, Southampton and Surrey Universities in the next 4 years. Although such projects strive to produce new techniques of various kinds, the software reviewed here could also influence, shape and help to integrate the algorithmic outcome of all 16 projects awarded within the EPSRC Autonomous and Intelligent Systems programme early 2012. To avoid mis-representation of technololgies provided by the software producer companies listed, most of this review is based on using quotes from original product descriptions

The golog programming language and agency

In this paper, we present our initial experiences modeling agency in the situation calculus and the Golog programming language. We describe the problems we have faced and discuss some research issues that remain to be addressed in the future. As an application of this research line, we propose an axiomatization of the robot Charles and the Fantastic City in the situation calculus as well as a controller written in Golog.Eje: Inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI

The golog programming language and agency

In this paper, we present our initial experiences modeling agency in the situation calculus and the Golog programming language. We describe the problems we have faced and discuss some research issues that remain to be addressed in the future. As an application of this research line, we propose an axiomatization of the robot Charles and the Fantastic City in the situation calculus as well as a controller written in Golog.Eje: Inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI

MASL: a Language for Multi-Agent System

The classical approach for Multi-Agent System (MAS) Control, especially autonomous and robotic ones, deals first from a microscopic point of view: each agent embed a control program with communication/synchronization primitives that enable cooperation between agents. The emergence of a global behaviour from a macroscopic point of view can only be observed afterwards. In this context, MASL offers a macroscopic and unified approach with heterogeneous and distributed calculations over deliberative, reactive or hybrid agents. In this high level language, regardless of the runtime, each concurrent agent locally decides its participation in a collective execution block named an e-block. Each e-block is an anonymous collective program that runs over an agent network following local conditions. The orchestral mode (scalar, asynchronous, synchronous) is statically fixed by a shared block attribute. The communication use shared memory, events, synchronous messages passing, and asynchronous messages passing. Heterogeneous agents are managed with heritage and polymorphism. Permeability mechanism, dealing with agent autonomy, allows an agent to dynamically filter calls to its interface in respects to the sender position in the e-block hierarchy. In dynamic task allocation of agents, auto failover and recovery, agent replacement in a robot fleet (case of agent failure, loss of a mandatory functionality for the mission) an e-block is an entry point of a collaborative work. In the case of synchronous e-block, the programming paradigm is the data parallel model with iterative task for waves of agents. Finally, MASL offers advances in the field of MAS (dynamic belonging to groups, accuracy of the pace of actions to undertake to enable a desired cooperation) and for the management of errors

Logic programming for deliberative robotic task planning

Over the last decade, the use of robots in production and daily life has increased. With increasingly complex tasks and interaction in different environments including humans, robots are required a higher level of autonomy for efficient deliberation. Task planning is a key element of deliberation. It combines elementary operations into a structured plan to satisfy a prescribed goal, given specifications on the robot and the environment. In this manuscript, we present a survey on recent advances in the application of logic programming to the problem of task planning. Logic programming offers several advantages compared to other approaches, including greater expressivity and interpretability which may aid in the development of safe and reliable robots. We analyze different planners and their suitability for specific robotic applications, based on expressivity in domain representation, computational efficiency and software implementation. In this way, we support the robotic designer in choosing the best tool for his application

On the Decidability of Verifying LTL Properties of Golog Programs: Extended Version

Golog is a high-level action programming language for controlling autonomous agents such as mobile robots. It is defined on top of a logic-based action theory expressed in the Situation Calculus. Before a program is deployed onto an actual robot and executed in the physical world, it is desirable, if not crucial, to verify that it meets certain requirements (typically expressed through temporal formulas) and thus indeed exhibits the desired behaviour. However, due to the high (first-order) expressiveness of the language, the corresponding verification problem is in general undecidable. In this paper, we extend earlier results to identify a large, non-trivial fragment of the formalism where verification is decidable. In particular, we consider properties expressed in a first-order variant of the branching-time temporal logic CTL*. Decidability is obtained by (1) resorting to the decidable first-order fragment C² as underlying base logic, (2) using a fragment of Golog with ground actions only, and (3) requiring the action theory to only admit local effects.In this extended version we extend the decidability result for the verification problem to the temporal logic CTL* over C2-axioms

Approaches for action sequence representation in robotics: a review

Robust representation of actions and its sequences for complex robotic tasks would transform robot’s understand- ing to execute robotic tasks efficiently. The challenge is to under- stand action sequences for highly unstructured environments and to represent and construct action and action sequences. In this manuscript, we present a review of literature dealing with representation of action and action sequences for robot task planning and execution. The methodological review was conducted using Google Scholar and IEEE Xplore, searching the specific keywords. This manuscript gives an overview of current approaches for representing action sequences in robotics. We propose a classification of different methodologies used for action sequences representation and describe the most important aspects of the reviewed publications. This review allows the reader to understand several options that do exist in the research community, to represent and deploy such action representations in real robots