Semantic Attachments for Domain-Independent Planning Systems

Dornhege, Christian; Eyerich, Patrick; Keller, Thomas; Trüg, Sebastian; Brenner, Michael; Nebel, Bernhard

doi:10.1007/978-3-642-25116-0_9

Cited by 94 publications

(123 citation statements)

References 16 publications

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“…Using a hierarchical top-down approach, a plan is generated first and then mapped onto low-level planners assuming that the symbolic abstraction, i.e. the world model and selected actions, are correct [24]. The problem with this approach is that a particular choice on the task planner level can cause the low-level planner to fail, e.g.…”

Section: Planner Integrationmentioning

confidence: 99%

“…Using a hierarchical bottom up approach, all information that is possibly relevant to the task planner is precomputed by the low-level planners, e.g. all possible paths are determined and provided to the task planner which then determines a set of valid actions [24]. This is unfeasible for planning problems involving articulated manipulators.…”

Section: Planner Integrationmentioning

confidence: 99%

“…Gravot et al do not try to identify a general interface between task planning and path planning, but provide a very specialized solution to their planning task. Dornhege et al take first steps towards making symbolic planners applicable to real-world problems [24], [25]. A robotic manipulation planning problem is decomposed into a symbolic and a geometric part.…”

Section: Task Planning For Robotics Applicationsmentioning

confidence: 99%

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Knowledge Representations for Planning Manipulation Tasks

Zacharias

2012

Cognitive Systems Monographs

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A complex manipulation task for a robot has to be planned on different levels of abstraction before it can be executed on a real system. At a high-level of abstraction, a task planner generates a sequence of subtasks from a given abstract command, its pre-and postconditions and a current world model. To restrict the already huge search space of the task planner, aspects like geometric information are not contained in the world model at this level. The task planner then assigns the subtasks to planners on a lower level of abstraction like path planners or grasp planners. These planners rely on geometric information to compute their solutions. However, without considering geometric information the task planner cannot determine good parameters for these low-level planners. Therefore, the derived plans may not be valid for a given situation and may require backtracking. Knowledge representations can bridge the gap between these planning levels and thereby enable scene reasoning. The kinematic capabilities of a robot are one aspect the task planner has to be aware of. Therefore this thesis introduces a novel general representation of the kinematic capabilities of a robot arm. The versatile workspace is defined to describe in which orientations the end effector attached to a robot arm can reach a position. The capability map is a calculable representation of the versatile workspace that allows to determine how well regions of the workspace are reachable. It accurately represents the versatile workspace of arbitrary arm kinematics and enables autonomous taskspecific reasoning. Furthermore, its visualization scheme is intuitively comprehensible for the human. The versatile applicability of the capability map is shown by examples from several distinct application domains. In human-robot interaction, the capability map is used to objectively evaluate a bi-manual interface for tele-operation. The results can also supplement the design process for humanoid robot design. In low-level geometric planning, the capability map is used to reduce the search space and to parameterize path planners and grasp planners. Thus, in a manipulation task for a humanoid robot more human-like motion is planned while simultaneously the computation time is reduced. In high-level task reasoning, the capability map is used to evaluate how well a robot is suited for a task. In an example a humanoid robot has to perform a task involving 3D trajectories. Regions are extracted from the capability map that permit the task execution and the suitability of the robot is inferred.

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Section: Planner Integrationmentioning

confidence: 99%

Section: Planner Integrationmentioning

confidence: 99%

Section: Task Planning For Robotics Applicationsmentioning

confidence: 99%

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Knowledge Representations for Planning Manipulation Tasks

Zacharias

2012

Cognitive Systems Monographs

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“…In previous work we have presented a new approach to solve such types of problems: The use of semantic attachments [5]. A semantic attachment is an external procedure called during the planning process to evaluate specific conditions or to directly alter the planning state.…”

Section: Planning With External Modulesmentioning

confidence: 99%

Task Planning for an Autonomous Service Robot

Keller

Eyerich

Nebel

2012

Springer Tracts in Advanced Robotics

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Abstract. In the DESIRE project an autonomous robot capable of performing service tasks in a typical kitchen environment has been developed. The overall system consists of various loosely coupled subcomponents providing particular features like manipulating objects or recognizing and interacting with humans. To bring all these subcomponents together to act as monolithic system, a high-performance planning system has been implemented. In this paper, we present this system's basic architecture and some advanced extensions necessary to cope with the various challenges arising in dynamic and uncertain environments like those a real world service robot is usually faced with.

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“…The approach of Dornhege et al [7] also integrates external components -so-called semantic attachments -into the planning process. However, semantic attachments do not directly consider multimodal perception as a source of external information, but mainly aims at the integration of high-level general purpose symbolic planning and domain specific lower-level reasoning (e.g., path or motion planning).…”

Section: Open World Robot Planningmentioning

confidence: 99%

Multimodal integration processes in plan-based service robot control

Off

Zhang

2011

Tinshhua Sci. Technol.

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Cross-modal integration processes are essential for service robots to reliably perceive relevant parts of the partially known unstructured environment. We demonstrate how multimodal integration on different abstraction levels leads to reasonable behavior that would be difficult to achieve with unimodal approaches. Sensing and acting modalities are composed to multimodal robot skills via a fuzzy multisensor fusion approach. Single modalities constitute basic robot skills that can dynamically be composed to appropriate behavior by symbolic planning. Furthermore, multimodal integration is exploited to answer relevant queries about the partially known environment. All these approaches are successfully implemented and tested on our mobile service robot platform TASER.

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Semantic Attachments for Domain-Independent Planning Systems

Cited by 94 publications

References 16 publications

Knowledge Representations for Planning Manipulation Tasks

Knowledge Representations for Planning Manipulation Tasks

Task Planning for an Autonomous Service Robot

Multimodal integration processes in plan-based service robot control

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