The dd&amp;p Robot Control Architecture

In the future, autonomous mobile robots will provide services in human's daily life. In the long run, these robots should be acting in the normal private or working environments of humans. Autonomy is one important aspect in the design of such robots because the robots should be able to act reasonably in changing environments. Robot control architectures based on local reactive behaviors have been established for supporting autonomy of mobile robots and have been successfully applied in laboratory and edutainment environments. When being used in human's private or working environments, safety (e.g. strict collision avoidance) and target-orientation are further major requirements on a mobile robot. Target-orientation means that the robot should, besides reacting on its immediate local environment, also be able to pursue long term targets such as reaching a certain destination. The work reported in this paper investigates the use of a behavior-based architecture on a mobile robot for making the robot applicable in a normal office environment. Complex behaviors for acting in this environment are being developed and are combined in a target-oriented way, thus overcoming the limitations of pure local reactivity. Experiments show the feasibility of the approach.

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“…As an extension, interfacing Dual Dynamics with the high-level planner provided by DD&P [12] will provide access to the planning layer.…”

Section: Resultsmentioning

confidence: 99%

“…These two variables are defined as nonlinear functions of inputs from sensors or sensor-filters (aggregated sensor values), external sources e.g. databases and especially of α T LLB , and α T HLB , see [12] for details. The HLBs implement only the activation function.…”

Section: The Dual-dynamics Architecturementioning

confidence: 99%

Target-oriented mobile robot behaviors for office navigation tasks

Hartanto

Schönherr

Mock

et al. 2004

Second IEEE Workshop on Software Technologies for Future Embedded and Ubiquitous Systems, 2004. Proceedings.

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“…Figure 2.1 compares the reactive and deliberative approaches. These include Autonomous Robot Architecture (AuRA) [48], Reactive Action Package (rap) [52], Task Control Architecture (tca) [53], Saphira [54], and DD&P [55]. The first AI robot, Shakey, at Stanford University used this paradigm [51].…”

Section: A Brief Overview Of Robot Control Architecturesmentioning

confidence: 99%

A Hybrid Deliberative Layer for Robotic Agents

Hartanto

2011

Lecture Notes in Computer Science

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Cognitive robots are all over the place. Well, at least that is what it looks like in research lab agendas on the planet.Some basic and fundamental problems in controlling mobile robots have been quite well understood in recent years: Localization and map building are chief examples. Now, as autonomous mobility as such is much less of a challenge, research resumes an activity that has started about half a century ago in mainstream AI; that got out of the AI mainstream for a while, as other challenges turned out to offer solutions faster; that got a little mocked for some time ("good old-fashioned AI", gofai); yet that has remained a fascinating scientific problem, and potentially a rich source of application projects: algorithmic models for goal-directed physical action in the world.So in a sense, very recent and ambitious projects in cognitive robotics, or cognitive technical systems, or robot cognition, or whatever you prefer to call them, are taking up that thread, which, I would say, goes back to the pioneering shakey project in the AI of the 1960s, and has remained unresolved ever since. However, there are a number of interesting differences between thinking about a cognitive robot in the 1960s and doing so today: Our modern computers are nearly infinitely more powerful; sensors are much better; decent robot hardware has become affordable even for a normal university lab; and, the proper share of AI: 50 years of AI research has yielded quite a number of wellunderstood algorithms and formalisms for planning, knowledge representation and reasoning that were unknown in the early days.And still, getting a cognitive robot to work is a challenge -which is why cognitive robots are not yet all over the place, and the cognition in those that are may fail to impress. Among a zoo of problems from "just" technical (integration!) to big AI problem (symbol grounding!) is a specimen that has to do with the proper AI share of the story: Using a planner or reasoner within the control software of an autonomous cognitive robot is different from using them in an off-line or human-in-the-loop system. Now this is the point where Ronny Hartanto's thesis comes into play. A robot working, for example, in a mundane household domain, would need to May 2011Joachim Hertzberg PrefaceAction planning has been used in the field of robotics for solving long-running tasks. In the robot architectures field, it is also known as the deliberative layer. However, there is still a gap between the symbolic representation on the one hand and the low-level control and sensor representation on the other. In addition, the definition of a planning problem for a complex, real-world robot is not trivial. The planning process could become intractable as its search spaces become large. Since the defined planning problem determines the complexity and the computability for solving the problem, it should contain only relevant states. In this work, a novel approach which amalgamates description logic (dl) reasoning with hierarchical task network (htn) planning i...

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“…Work that is not directly focused on fault detection and isolation, but still related to execution monitoring is the work on the Dual Dynamics & Planning (DD&P) robot control architecture, see [35,72]. This work is related to execution monitoring since the DD&P architecture has an interesting technique for extracting information about the robot and its performance.…”

Section: Expert Systemsmentioning

confidence: 99%

Execution monitoring in robotics: A survey

Pettersson

2005

Robotics and Autonomous Systems

146

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Research on execution monitoring in its own is still not very common within the field of robotics and autonomous systems. It is more common that researchers interested in control architectures or execution planning include monitoring as a small part of their work when they realize that it is needed. On the other hand, execution monitoring has been a well studied topic within industrial control, although control theorists seldom use this term. Instead they refer to the problem of fault detection and isolation (FDI). This survey will use the knowledge and terminology from industrial control in order to classify different execution monitoring approaches applied to robotics. The survey is particularly focused on autonomous mobile robotics.

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The dd&p Robot Control Architecture

Cited by 4 publications

References 18 publications

Target-oriented mobile robot behaviors for office navigation tasks

Target-oriented mobile robot behaviors for office navigation tasks

A Hybrid Deliberative Layer for Robotic Agents

Execution monitoring in robotics: A survey

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