Spatial language for route-based humanoid robot navigation

Elmogy, Mohammed; Habel, Christopher; Zhang, Jianwei

doi:10.1007/s10339-009-0290-y

Cited by 4 publications

(4 citation statements)

References 12 publications

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“…Other studies have focused on developing a language to give instructions to the robot [54,55]. These researches present a spatial language, called route instruction language (RIL), to describe the route between the start and the end points of a humanoid robot's navigation task.…”

Section: Navigation and Human-robot Interactionmentioning

confidence: 99%

Waymarking in Social Robots: Environment Signaling Using Human–Robot Interaction

Corrales-Paredes

Malfáz

Egido-García

et al. 2021

Sensors

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Travellers use the term waymarking to define the action of posting signs, or waymarks, along a route. These marks are intended to be points of reference during navigation for the environment. In this research, we will define waymarking as the skill of a robot to signal the environment or generate information to facilitate localization and navigation, both for its own use and for other robots as well. We present an automated environment signaling system using human–robot interaction and radio frequency identification (RFID) technology. The goal is for the robot, through human–robot interaction, to obtain information from the environment and use this information to carry out the signaling or waymarking process. HRI will play a key role in the signaling process since this type of communication makes it possible to exchange more specific and enriching information. The robot uses common phrases such as “Where am I?” and “Where can I go?”, just as we humans do when we ask other people for information about the environment. It is also possible to guide the robot and “show” it the environment to carry out the task of writing the signs. The robot will use the information received to create, update, or improve the navigation data in the RFID signals. In this paper, the signaling process will be described, how the robot acquires the information for signals, writing and updating process and finally, the implementation and integration in a real social robot in a real indoor environment.

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Section: Navigation and Human-robot Interactionmentioning

confidence: 99%

Waymarking in Social Robots: Environment Signaling Using Human–Robot Interaction

Corrales-Paredes

Malfáz

Egido-García

et al. 2021

Sensors

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“…At the beginning, the user verbally describes the route to the robot by using our route instruction language (RIL) [20]. Then, the route instructions are parsed and analyzed by the instruction interpreter to present the motion actions, spatial relationships, and landmarks in a symbolic representation.…”

Section: System Architecturementioning

confidence: 99%

Online motion planning for HOAP-2 humanoid robot navigation

Elmogy

Habel

Zhang

2009

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-Autonomous robot navigation is becoming an increasingly important research topic for mobile robots. In the last few years, significant progress has been made towards stable robotic bipedal walking. This is creating an increased research interest in developing autonomous navigation strategies which are tailored specifically to humanoid robots. Efficient approaches to perception and motion planning, which are suited to the unique characteristics of biped humanoid robots and their typical operating environments, are receiving special interest. In this paper, we present a time-efficient motion planning system for a Fujitsu HOAP-2 humanoid robot. The sampling based algorithm is used to provide the robot with minimal free configuration space which is sampled to extract the robot path. For collision detection, a cylinder model is used to approximate the trajectory for the body center of the humanoid robot during navigation. It calculates the actual distances required to execute different actions of the robot and compares them with the distances to the nearest obstacles. The A* search algorithm is then implemented to find smooth and low-cost footstep placements of the humanoid robot within the resulting configuration space. The proposed hybrid algorithm reduces searching time and produces a smoother path for the humanoid robot at a low cost.

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“…In our system, we present a spatial language -called Route Instruction Language (RIL) [15] -to describe route-based navigation tasks for a mobile robot. This language is implemented to present an intuitive interface that will enable novice users to easily and naturally describe a route to a mobile robot in indoor and miniature city environments.…”

Section: Route Instruction Language (Ril)mentioning

confidence: 99%

A Cognitively Motivated Route-Interface for Mobile Robot Navigation

Elmogy

Habel

Zhang

2009

Cognitive Systems Monographs

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A more natural interaction between humans and mobile robots can be achieved by bridging the gap between the format of spatial knowledge used by robots and the format of languages used by humans. This enables both sides to communicate by using shared knowledge. Spatial knowledge can be (re)presented in various ways to increase the interaction between humans and mobile robots. One effective way is to describe the route verbally to the robot. This method can permit computer language-naive users to instruct mobile robots, which understand spatial descriptions, to naturally perform complex tasks using succinct and intuitive commands. We present a spatial language to describe route-based navigation tasks for a mobile robot. The instructions of this spatial language are implemented to provide an intuitive interface with which novice users can easily and naturally describe a navigation task to a mobile robot in a miniature city or in any other indoor environment. In our system, the instructions of the processed route are analyzed to generate a symbolic representation via the instruction interpreter. The resulting symbolic representation is supplied to the robot motion planning stage as an initial path estimation of route description and it is also used to generate a topological map of the route's environment.

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Spatial language for route-based humanoid robot navigation

Cited by 4 publications

References 12 publications

Waymarking in Social Robots: Environment Signaling Using Human–Robot Interaction

Waymarking in Social Robots: Environment Signaling Using Human–Robot Interaction

Online motion planning for HOAP-2 humanoid robot navigation

A Cognitively Motivated Route-Interface for Mobile Robot Navigation

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