17,954 research outputs found
Creating Interaction Scenarios With a New Graphical User Interface
The field of human-centered computing has known a major progress these past
few years. It is admitted that this field is multidisciplinary and that the
human is the core of the system. It shows two matters of concern:
multidisciplinary and human. The first one reveals that each discipline plays
an important role in the global research and that the collaboration between
everyone is needed. The second one explains that a growing number of researches
aims at making the human commitment degree increase by giving him/her a
decisive role in the human-machine interaction. This paper focuses on these
both concerns and presents MICE (Machines Interaction Control in their
Environment) which is a system where the human is the one who makes the
decisions to manage the interaction with the machines. In an ambient context,
the human can decide of objects actions by creating interaction scenarios with
a new visual programming language: scenL.Comment: 5th International Workshop on Intelligent Interfaces for
Human-Computer Interaction, Palerme : Italy (2012
Graphical programming and the use of simulation for space-based manipulators
Robotic manipulators are difficult to program even without the special requirements of a zero-gravity environment. While attention should be paid to investigating the usefulness of industrial application programming methods to space manipulators, new methods with potential application to both environments need to be invented. These methods should allow various levels of autonomy and human-in-the-loop interaction and simple, rapid switching among them. For all methods simulation must be integrated to provide reliability and safety. Graphical programming of manipulators is a candidate for an effective robot programming method despite current limitations in input devices and displays. A research project in task-level robot programming has built an innovative interface to a state-of-the-art commercial simulation and robot programming platform. The prototype demonstrates simple augmented methods for graphical programming and simulation which may be of particular interest to those concerned with Space Station applications; its development has also raised important issues for the development of more sophisticated robot programming tools. Both aspects of the project are discussed
A component-oriented programming framework for developing embedded mobile robot software using PECOS model
A practical framework for component-based software engineering of embedded real-time systems, particularly for autonomous mobile robot embedded software development using PECOS component model is proposed The main features of this framework are: (1) use graphical representation for components definition and composition; (2) target C language for optimal code generation with small micro-controller; and (3) does not requires run-time support except for real-time kernel. Real-time implementation indicates that, the PECOS component model together with the proposed framework is suitable for resource constrained embedded systems
Bayesian robot Programming
We propose a new method to program robots based on Bayesian inference and learning. The capacities of this programming method are demonstrated through a succession of increasingly complex experiments. Starting from the learning of simple reactive behaviors, we present instances of behavior combinations, sensor fusion, hierarchical behavior composition, situation recognition and temporal sequencing. This series of experiments comprises the steps in the incremental development of a complex robot program. The advantages and drawbacks of this approach are discussed along with these different experiments and summed up as a conclusion. These different robotics programs may be seen as an illustration of probabilistic programming applicable whenever one must deal with problems based on uncertain or incomplete knowledge. The scope of possible applications is obviously much broader than robotics
Improving the Parallel Execution of Behavior Trees
Behavior Trees (BTs) have become a popular framework for designing
controllers of autonomous agents in the computer game and in the robotics
industry. One of the key advantages of BTs lies in their modularity, where
independent modules can be composed to create more complex ones. In the
classical formulation of BTs, modules can be composed using one of the three
operators: Sequence, Fallback, and Parallel. The Parallel operator is rarely
used despite its strong potential against other control architectures as Finite
State Machines. This is due to the fact that concurrent actions may lead to
unexpected problems similar to the ones experienced in concurrent programming.
In this paper, we introduce Concurrent BTs (CBTs) as a generalization of BTs in
which we introduce the notions of progress and resource usage. We show how CBTs
allow safe concurrent executions of actions and we analyze the approach from a
mathematical standpoint. To illustrate the use of CBTs, we provide a set of use
cases in robotics scenarios
Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study
Developing robot agnostic software frameworks involves synthesizing the
disparate fields of robotic theory and software engineering while
simultaneously accounting for a large variability in hardware designs and
control paradigms. As the capabilities of robotic software frameworks increase,
the setup difficulty and learning curve for new users also increase. If the
entry barriers for configuring and using the software on robots is too high,
even the most powerful of frameworks are useless. A growing need exists in
robotic software engineering to aid users in getting started with, and
customizing, the software framework as necessary for particular robotic
applications. In this paper a case study is presented for the best practices
found for lowering the barrier of entry in the MoveIt! framework, an
open-source tool for mobile manipulation in ROS, that allows users to 1)
quickly get basic motion planning functionality with minimal initial setup, 2)
automate its configuration and optimization, and 3) easily customize its
components. A graphical interface that assists the user in configuring MoveIt!
is the cornerstone of our approach, coupled with the use of an existing
standardized robot model for input, automatically generated robot-specific
configuration files, and a plugin-based architecture for extensibility. These
best practices are summarized into a set of barrier to entry design principles
applicable to other robotic software. The approaches for lowering the entry
barrier are evaluated by usage statistics, a user survey, and compared against
our design objectives for their effectiveness to users
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