Extracting navigation states from a hand-drawn map

Skubic, M.; Matsakis, Pascal; Forrester, Bruce; Chronis, G.

doi:10.1109/robot.2001.932563

Cited by 20 publications

(23 citation statements)

References 11 publications

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“…The Command Interpreter produces semantic interpretations of the commands in a structure which we call a context predicate 4 . Consider the following dialog (1) which is mapped into a context predicate (2).…”

Section: The Semantics Of Spatial Language and Linguistic Consequmentioning

confidence: 99%

“…First, using sonar sensors on a mobile robot, a model of the environment was built, and a spatial description of that environment was generated, providing linguistic communication from the robot to the human [3]. Second, a hand-drawn map was sketched on a Personal Digital Assistant (PDA), as a means of communicating a navigation task to a robot [4]. The sketch, which represented an approximate map, was analyzed using spatial reasoning, and the navigation task was extracted as a sequence of spatial navigation states.…”

Section: Introductionmentioning

confidence: 99%

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Spatial Language for Human-Robot Dialogs

Skubic¹,

Perzanowski²,

Blisard³

et al. 2003

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Report Documentation PageForm Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. The original document contains color images. REPORT DATE ABSTRACTIn conversation, people often use spatial relationships to describe their environment, e.g., "There is a desk in front of me and a doorway behind it", and to issue directives, e.g., "Go around the desk and through the doorway." In our research, we have been investigating the use of spatial relationships to establish a natural communication mechanism between people and robots, in particular, for novice users. In this paper, the work on robot spatial relationships is combined with a multi-modal robot interface. We show how linguistic spatial descriptions and other spatial information can be extracted from an evidence grid map and how this information can be used in a natural, human-robot dialog. Examples using spatial language are included for both robot-to-human feedback and also human-to-robot commands. We also discuss some linguistic consequences in the semantic representations of spatial and locative information based on this work. AbstractIn conversation, people often use spatial relationships to describe their environment, e.g., "There is a desk in front of me and a doorway behind it", and to issue directives, e.g., "Go around the desk and through the doorway." In our research, we have been investigating the use of spatial relationships to establish a natural communication mechanism between people and robots, in particular, for novice users.In this paper, the work on robot spatial relationships is combined with a multi-modal robot interface. We show how linguistic spatial descriptions and other spatial information can be extracted from an evidence grid map and how this information can be used in a natural, human-robot dialog. Examples using spatial language are included for both robot-to-human feedback and also human-to-robot commands. We also discuss some linguistic consequences in the semantic representations of spatial and locative information based on this work.

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Section: The Semantics Of Spatial Language and Linguistic Consequmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial Language for Human-Robot Dialogs

Skubic¹,

Perzanowski²,

Blisard³

et al. 2003

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show abstract

“…Spatial reasoning is accomplished using the histogram of forces [11], as described in previous work [3,4,5,12]. For each object, two histograms are computed (the histograms of constant forces and gravitational forces), which represent the relative spatial position between that object and the robot.…”

Section: Generating Spatial Language From Occupancy Grid Mapsmentioning

confidence: 99%

“…An example of the generated descriptions is shown in Figure 4(c). See [3,4,5] and especially [12] for additional details. …”

Section: Generating Spatial Language From Occupancy Grid Mapsmentioning

confidence: 99%

“…First, using sonar sensors on a mobile robot, a model of the environment was built, and a spatial description of that environment was generated, providing linguistic communication from the robot to the user [3]. Second, a hand-drawn map was sketched on a PDA, as a means of communicating a navigation task to a robot [4]. The sketch, which represented an approximate map, was analyzed using spatial reasoning, and the navigation task was extracted as a sequence of spatial navigation states.…”

Section: Introductionmentioning

confidence: 99%

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Using Spatial Language in a Human-Robot Dialog

Skubic¹,

Perzanowski²,

Schultz³

et al. 2002

PsycEXTRA Dataset

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In conversation, people often use spatial relationships to describe their environment, e.g., "There is a desk in front of me and a doorway behind it", and to issue directives, e.g., "Go around the desk and through the doorway." In our research, we have been investigating the use of spatial relationships to establish a natural communication mechanism between people and robots, in particular, for novice users. In this paper, the work on robot spatial relationships is combined with a multimodal robot interface developed at the Naval Research Lab. We show how linguistic spatial descriptions and other spatial information can be extracted from an evidence grid map and how this information can be used in a natural, human-robot dialog.

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Beyond 2001: The Linguistic Spatial Odyssey

Fogel¹,

Robinson²

2009

Computational Intelligence

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Why is it so hard to talk to a machine? If only we could communicate in a natural human language with robots, they would be so much more useful. Having machines that can reason spatially and receive and communicate such reasoning linguistically will extend their utility in many more scenarios that are dangerous, tedious, unhealthy, etc. Scene description, involving linguistic expressions of the spatial relationships between image objects, is a major goal of high-level computer vision. People have studied spatial relationships for several years. In a series of papers, we have introduced the use of histograms of forces to produce evidence for the description of relative position of objects in a digital image. There is a parameterized family of such histograms, for example, the histogram of constant forces (much like the earlier histogram of angles) and the histogram of gravitational forces that highlights areas that are close between the two objects. Utilizing the fuzzy directional membership information extracted from these histograms within fuzzy logic rule-based systems, we have produced high-level linguistic descriptions of natural scenes as viewed by an external observer. Additionally, we have begun to exploit the theoretical properties of the histograms to match images that may be the same scene viewed under different pose conditions. In fact, we can even recover estimates of the pose parameters. These linguistic descriptions have then been brought into an ego-centered viewpoint for application to robotics. We describe three initial activities here: production of linguistic scene description from a mobile robot standpoint, spatial language for human/robot communication, and understanding of a sketched route map for communicating navigation routes to robots. These efforts just scratch the surface of the potential applications and we end with future projections.

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Extracting navigation states from a hand-drawn map

Cited by 20 publications

References 11 publications

Spatial Language for Human-Robot Dialogs

Spatial Language for Human-Robot Dialogs

Using Spatial Language in a Human-Robot Dialog

Beyond 2001: The Linguistic Spatial Odyssey

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