A New Efficiency-Weighted Strategy for Continuous Human/Robot Cooperation in Navigation

Poncela, A.; García, Cristina; Pérez, Eduardo; Hernández, Francisco

doi:10.1109/tsmca.2009.2013191

Cited by 45 publications

(32 citation statements)

References 29 publications

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“…In [36] the authors consider how to share the navigational task between a human and a robot. Rather than making either dominant, thus being able to override the other, the action of the robot is a synthesis of the commands chosen by both the human and the robot.…”

Section: Assistance In Navigationmentioning

confidence: 99%

Group abstraction for assisted navigation of social activities in intelligent environments

Given-Wilson

Legay

Sedwards

et al. 2018

J Reliable Intell Environ

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The ACANTO project is developing robotic assistants to aid the confidence and recovery of older adults. A key requirement of these assistants is aiding with navigation in complex and potentially chaotic environments. Prior work has addressed this for a single user, using a single robotic assistant in an intelligent environment. However, for therapeutic purposes, ACANTO supports social groups and group activities. ACANTO's robotic assistants must therefore be able to plan the motion of groups of older adults walking together. This requires an efficient navigation solution that can handle large numbers of users and that can operate rapidly on embedded computing devices. To increase user confidence, the solution must encourage group cohesion without trying to impose its own rigid structure; it must try to maintain the natural (de facto) group structure despite unpredictable behaviours and environmental conditions. Our on-the-fly group motion planner addresses these challenges by: using intelligent environment information to develop behavioural traces, clustering traces to determine groups, constructing a predictive model of the groups as a whole, and finding an optimal suggested trajectory using Statistical Model Checking. In this work we describe our proposed approach in detail and validate some of its novel aspects on the ETH Zürich pedestrian motion dataset.

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Section: Assistance In Navigationmentioning

confidence: 99%

Group abstraction for assisted navigation of social activities in intelligent environments

Given-Wilson

Legay

Sedwards

et al. 2018

J Reliable Intell Environ

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“…Linear blending has enjoyed wide adoption in the assistive wheelchair community [10], [58], [38], [57], [61], [47], [56], [35]. In [48], [59], an even broader adoption of linear blending is advocated. These three examples are a small sample of the use cases of linear blending; a more comprehensive bibliographic accounting is found in [23], [22].…”

Section: Related Workmentioning

confidence: 99%

Breaking the Human-Robot Deadlock: Surpassing Shared Control Performance Limits with Sparse Human-Robot Interaction

Trautman

2017

Robotics: Science and Systems XIII

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Abstract-Human machine teaming has, for decades, been conceptualized as a function allocation (FA) or levels of autonomy (LOA) process: the human is suited for some tasks, while the machine is suitable for others, and as machines improve they take over duties previously assigned to humans. A wide variety of methods-including adaptive, adjustable, blended, supervisory and mixed initiative control, implemented discretely or continuously, as potential fields, as virtual fixture interfaces, or haptic interfaces-are derivatives of FA/LOA. We formalize FA/LOA (and all their derivatives) under a single mathematical formulation called classical shared control (CSC). Despite the widespread adoption of CSC, we prove that it fails to optimize human and robot agreement and intent if either the human or robot model displays "intention ambiguity" (e.g., the human's intended goal is unclear or the robot finds multiple viable solutions). Practically, this suboptimality can manifest as unnecessary and unresolvable disagreement (an unnecessary deadlock). For instance, if the robot chooses to go left around an obstacle and the human chooses to go right, CSC only provides two solutions: freeze in place or collide with the obstacle (we provide a wide variety of failure examples in [52], https://arxiv.org/abs/1611.09490). We find that CSC suboptimality stems from arbitrating over model samples, rather than over models. Our key insight is thus to arbitrate over human and robot distributions; we prove this method optimizes human and robot agreement and intent and resolves deadlocking. Our key contribution is computationally efficient distribution arbitration: if the human and robot carry N our joint has fewer modes than the individual agent models. We call our approach N min -sparse generalized shared control.

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“…Furthermore, knowledge representation can be utilized in intricate task planning at both abstract and semantic levels, as well as for motion and manipulation planning at a geometric level [17]. To collaborate with humans, on the other hand, semantic representation of space is required [27]- [29]. Ontology can be used for spatial representation and navigation through a spatial semantic hierarchy (SSH) [18] and route graphs (RG) [19] representing the general concepts of space.…”

Section: B Related Workmentioning

confidence: 99%

Ontology-Based Unified Robot Knowledge for Service Robots in Indoor Environments

Lim

Suh

2011

IEEE Trans. Syst., Man, Cybern. A

140

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Abstract-A significant obstacle for service robots is the execution of complex tasks in real environments. For example, it is not easy for service robots to find objects that are partially observable and are located at a place which is not identical but near the place where the robots saw them previously. To overcome the challenge effectively, robot knowledge represented as a semantic network can be extremely useful. This paper presents an ontology-based unified robot knowledge framework that integrates low-level data with high-level knowledge for robot intelligence. This framework consists of two sections: knowledge description and knowledge association. Knowledge description includes comprehensively integrated robot knowledge derived from low-level knowledge regarding perceptual features, part objects, metric maps, and primitive behaviors, as well as high-level knowledge about perceptual concepts, objects, semantic maps, tasks, and contexts. Knowledge association uses logical inference with both unidirectional and bidirectional rules. This characteristic enables reasoning to be performed even when only a partial information is available. The experimental results that demonstrate the advantages of using the proposed knowledge framework are also presented.Index Terms-Intelligent service robot, knowledge association, knowledge description, ontology-based knowledge, unified robot knowledge.

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A New Efficiency-Weighted Strategy for Continuous Human/Robot Cooperation in Navigation

Cited by 45 publications

References 29 publications

Group abstraction for assisted navigation of social activities in intelligent environments

Group abstraction for assisted navigation of social activities in intelligent environments

Breaking the Human-Robot Deadlock: Surpassing Shared Control Performance Limits with Sparse Human-Robot Interaction

Ontology-Based Unified Robot Knowledge for Service Robots in Indoor Environments

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