Tactile-Object Recognition From Appearance Information

Pezzementi, Zachary; Plaku, Erion; Reyda, Caitlin; Hager, Gregory D.

doi:10.1109/tro.2011.2125350

Cited by 137 publications

(122 citation statements)

References 39 publications

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“…They have been selected only based on the expertise of the authors and are not intended to endorse any claim of generality or importance. Other examples include continuous monitoring of temporal-spatial phenomena in partially known environments (e.g., ocean monitoring [28]), olfactory exploration [22], tactile exploration of object properties [25], information gathering [27], and pursuit/evasion [13].…”

Section: Navigation Strategiesmentioning

confidence: 99%

Moving From ‘How to go There?’ to ‘Where to go?’: Towards Increased Autonomy of Mobile Robots

Amigoni

Basilico

2014

New Trends in Medical and Service Robots

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Autonomous mobile robots have seen a wide spread development in recent years, due to their possible applications (e.g., surveillance and search and rescue). Several techniques have been proposed for solving the path planning problem, in which a user specifies spatial targets and the robots autonomously decide how to go there. In contrast, the problem of where to go next, in which the targets themselves are autonomously decided by the robots, is largely unexplored and lacking an assessed theoretical basis. In this work, we make a step towards a framework for casting and addressing this problem. The framework includes the following dimensions: the amount of knowledge about the environment the robots have, the kind of that knowledge, the criteria used to evaluate the success of the decisions, the number of decision makers, and the possible adversarial nature of the settings. We focus on applications relative to exploration and patrolling.

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Section: Navigation Strategiesmentioning

confidence: 99%

Moving From ‘How to go There?’ to ‘Where to go?’: Towards Increased Autonomy of Mobile Robots

Amigoni

Basilico

2014

New Trends in Medical and Service Robots

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“…Here the kinesthetic cues are similar to human proprioception that refers to the awareness of the positions and movements of the body parts. Though the tactile features extracted from the local regions have been extensively studied in the recent robotics research [2]- [5], the use of kinesthetic cues to recognize the global object shapes is still largely unexplored.…”

Section: Introductionmentioning

confidence: 99%

Iterative Closest Labeled Point for tactile object shape recognition

Luo

Mou

Althoefer

et al. 2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-Tactile data and kinesthetic cues are two important sensing sources in robot object recognition and are complementary to each other. In this paper, we propose a novel algorithm named Iterative Closest Labeled Point (iCLAP) to recognize objects using both tactile and kinesthetic information. The iCLAP first assigns different local tactile features with distinct label numbers. The label numbers of the tactile features together with their associated 3D positions form a 4D point cloud of the object. In this manner, the two sensing modalities are merged to form a synthesized perception of the touched object. To recognize an object, the partial 4D point cloud obtained from a number of touches iteratively matches with all the reference cloud models to identify the best fit. An extensive evaluation study with 20 real objects shows that our proposed iCLAP approach outperforms those using either of the separate sensing modalities, with a substantial recognition rate improvement of up to 18%.

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“…Actuation systems including some robots are now possible to perform a wide variety of operation with the development of motion control (1) . Due to the development of these robotics, control technologies, a system to replace the human motion has been studied a lot (2) .…”

Section: Introductionmentioning

confidence: 99%

High-Performance Force Control Based on Virtual Bilateral Control Structure

Miyagi

Katsura

2015

IEEJ Journal IA

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This paper proposes a new force control based on a bilateral control structure. Improvements in motion control technology, including force control, are important to realizing a human support robotic system. Conventionally, robot systems require high-precision positioning accuracy. In the near future, however, robots will need to be involved in human society directly. In this case, force control with high precision is an essential part of robot system control. For a complex system, raising the controller gain and bandwidth is not easy. In the proposed system, a virtual position control loop is constructed in a conventional force control to assist with ideal acceleration control. With the proposed system, high-accuracy force control and a control band can be achieved with superior performance compared to conventional systems.

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Tactile-Object Recognition From Appearance Information

Cited by 137 publications

References 39 publications

Moving From ‘How to go There?’ to ‘Where to go?’: Towards Increased Autonomy of Mobile Robots

Moving From ‘How to go There?’ to ‘Where to go?’: Towards Increased Autonomy of Mobile Robots

Iterative Closest Labeled Point for tactile object shape recognition

High-Performance Force Control Based on Virtual Bilateral Control Structure

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