57,483 research outputs found
Neural Task Programming: Learning to Generalize Across Hierarchical Tasks
In this work, we propose a novel robot learning framework called Neural Task
Programming (NTP), which bridges the idea of few-shot learning from
demonstration and neural program induction. NTP takes as input a task
specification (e.g., video demonstration of a task) and recursively decomposes
it into finer sub-task specifications. These specifications are fed to a
hierarchical neural program, where bottom-level programs are callable
subroutines that interact with the environment. We validate our method in three
robot manipulation tasks. NTP achieves strong generalization across sequential
tasks that exhibit hierarchal and compositional structures. The experimental
results show that NTP learns to generalize well to- wards unseen tasks with
increasing lengths, variable topologies, and changing objectives.Comment: ICRA 201
Computational tasks in robotics and factory automation
The design of Manufacturing Planning and Control Systems (MPCSs) ā systems that negotiate with Customers and Suppliers to exchange products in return for money in order to generate profit, is discussed.\ud
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The computational task of MPCS components are systematically specified as a starting point for the development of computational engines, as computer systems and programs, that execute the specified computation. Key issues are the overwhelming complexity and frequently changing application of MPCSs
A Local Logic for Realizability in Web Service Choreographies
Web service choreographies specify conditions on observable interactions
among the services. An important question in this regard is realizability:
given a choreography C, does there exist a set of service implementations I
that conform to C ? Further, if C is realizable, is there an algorithm to
construct implementations in I ? We propose a local temporal logic in which
choreographies can be specified, and for specifications in the logic, we solve
the realizability problem by constructing service implementations (when they
exist) as communicating automata. These are nondeterministic finite state
automata with a coupling relation. We also report on an implementation of the
realizability algorithm and discuss experimental results.Comment: In Proceedings WWV 2014, arXiv:1409.229
Procedure-modular specification and verification of temporal safety properties
This paper describes ProMoVer, a tool for fully automated procedure-modular verification of Java programs equipped with method-local and global assertions that specify safety properties of sequences of method invocations. Modularity at the procedure-level is a natural instantiation of the modular verification paradigm, where correctness of global properties is relativized on the local properties of the methods rather than on their implementations. Here, it is based on the construction of maximal models for a program model that abstracts away from program data. This approach allows global properties to be verified in the presence of code evolution, multiple method implementations (as arising from software product lines), or even unknown method implementations (as in mobile code for open platforms). ProMoVer automates a typical verification scenario for a previously developed tool set for compositional verification of control flow safety properties, and provides appropriate pre- and post-processing. Both linear-time temporal logic and finite automata are supported as formalisms for expressing local and global safety properties, allowing the user to choose a suitable format for the property at hand. Modularity is exploited by a mechanism for proof reuse that detects and minimizes the verification tasks resulting from changes in the code and the specifications. The verification task is relatively light-weight due to support for abstraction from private methods and automatic extraction of candidate specifications from method implementations. We evaluate the tool on a number of applications from the domains of Java Card and web-based application
From Specifications to Behavior: Maneuver Verification in a Semantic State Space
To realize a market entry of autonomous vehicles in the foreseeable future,
the behavior planning system will need to abide by the same rules that humans
follow. Product liability cannot be enforced without a proper solution to the
approval trap. In this paper, we define a semantic abstraction of the
continuous space and formalize traffic rules in linear temporal logic (LTL).
Sequences in the semantic state space represent maneuvers a high-level planner
could choose to execute. We check these maneuvers against the formalized
traffic rules using runtime verification. By using the standard model checker
NuSMV, we demonstrate the effectiveness of our approach and provide runtime
properties for the maneuver verification. We show that high-level behavior can
be verified in a semantic state space to fulfill a set of formalized rules,
which could serve as a step towards safety of the intended functionality.Comment: Published at IEEE Intelligent Vehicles Symposium (IV), 201
The formal, tool supported development of real time systems
The language SDL has long been applied in the development of various kinds of systems. Real-time systems are one application area where SDL has been applied extensively. Whilst SDL allows for certain modelling aspects of real-time systems to be represented, the language and its associated tool support have certain drawbacks for modelling and reasoning about such systems. In this paper we highlight the limitations of SDL and its associated tool support in this domain and present language extensions and next generation real-time system tool support to help overcome them. The applicability of the extensions and tools is demonstrated through a case study based upon a multimedia binding object used to support a configuration of time dependent information producers and consumers realising the so called lip-synchronisation algorithm
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