Classification of clothing using interactive perception

Willimon, Bryan; Birchfield, Stan; Walker, Ian D.

doi:10.1109/icra.2011.5980336

Cited by 85 publications

(69 citation statements)

References 25 publications

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“…In this way, the approach bears some resemblance to interactive perception [8], [9], [25], [26], [27], except that we allow a human to perform the interaction due to the specific constraints of articulated motion in our objects. Automatically planning the end effector motion path for interactive perception in such situations remains an unsolved problem, because a preliminary model (at least) is needed in order to interact with the object, but the interaction is necessary to estimate the model.…”

Section: Occlusion-aware Reconstructionmentioning

confidence: 99%

Occlusion-aware reconstruction and manipulation of 3D articulated objects

Huang

Walker

Birchfield

2012

2012 IEEE International Conference on Robotics and Automation

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Abstract-We present a method to recover complete 3D models of articulated objects. Structure-from-motion techniques are used to capture 3D point cloud models of the object in two different configurations. A novel combination of Procrustes analysis and RANSAC facilitates a straightforward geometric approach to recovering the joint axes, as well as classifying them automatically as either revolute or prismatic. With the resulting articulated model, a robotic system is able to manipulate the object along its joint axes at a specified grasp point in order to exercise its degrees of freedom. Because the models capture all sides of the object, they are occluded-aware, enabling the robotic system to plan paths to parts of the object that are not visible in the current view. Our algorithm does not require prior knowledge of the object, nor does it make any assumptions about the planarity of the object or scene. Experiments with a PUMA 500 robotic arm demonstrate the effectiveness of the approach on a variety of objects with both revolute and prismatic joints.

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Section: Occlusion-aware Reconstructionmentioning

confidence: 99%

Occlusion-aware reconstruction and manipulation of 3D articulated objects

Huang

Walker

Birchfield

2012

2012 IEEE International Conference on Robotics and Automation

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“…Unlike dressing assistance, recognition methods for clothing manipulation have been widely reported in the literature [6,19]. Because objects made of cloth are so flexible, observing their motions during manipulation is essential.…”

Section: Clothing-state Estimationmentioning

confidence: 99%

Bottom Dressing by a Dual-Arm Robot Using a Clothing State Estimation Based on Dynamic Shape Changes

Yamazaki

Oya²,

Nagahama³

et al. 2016

International Journal of Advanced Robotic Systems

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This paper describes an autonomous robot's method of dressing a subject in clothing. Our target task is to dress a person in the sitting pose. We especially focus on the action whereby a robot automatically pulls a pair of trousers up the subject's legs, an action frequently needed in dressing assistance. To avoid injuring the subject's legs, the robot should be able to recognize the state of the manipulated clothing. Therefore, while handling the clothing, the robot is supplied with both visual and tactile sensory information. A dressing failure is detected by the visual sensing of the behaviour of optical flows extracted from the clothing's movements. The effectiveness of the proposed approach is implemented and validated in a life-sized humanoid robot.

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“…Research on perception and manipulation tasks for robotic laundry systems consists of: isolating and classifying clothes from a laundry heap [8,5,9], finding a tractable state of the clothes in order to interact and manipulate them [3] and then folding the cloth [1,2,5]. In that regard, Ramisa et al [8] propose a supervised learning approach for grasping highly wrinkled garments.…”

Section: Literature Reviewmentioning

confidence: 99%

A Precise Method for Cloth Configuration Parsing Applied to Single-Arm Flattening

Sun

Aragon-Camarasa

Khan

et al. 2016

International Journal of Advanced Robotic Systems

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In this paper, we investigate the contribution that visual perception affords to a robotic manipulation task in which a crumpled garment is flattened by eliminating visually detected wrinkles. In order to explore and validate visually guided clothing manipulation in a repeatable and controlled environment, we have developed a hand-eye interactive virtual robot manipulation system that incorporates a clothing simulator to close the effector-garment-visual sensing interaction loop. We present the technical details and compare the performance of two different methods for detecting, representing and interpreting wrinkles within clothing surfaces captured in high-resolution depth maps. The first method we present relies upon a clustering-based method for localizing and parametrizing wrinkles, while the second method adopts a more advanced geometrybased approach in which shape-topology analysis underpins the identification of the cloth configuration (i.e., maps wrinkles). Having interpreted the state of the cloth configuration by means of either of these methods, a heuristicbased flattening strategy is then executed to infer the appropriate forces, their directions and gripper contact locations that must be applied to the cloth in order to flatten the perceived wrinkles. A greedy approach, which attempts to flatten the largest detected wrinkle for each perception-iteration cycle, has been successfully adopted in this work. We present the results of our heuristic-based flattening methodology which relies upon clustering-based and geometry-based features respectively. Our experiments indicate that geometry-based features have the potential to provide a greater degree of clothing configuration understanding and, as a consequence, improve flattening performance. The results of experiments using a real robot (as opposed to simulated robot) also confirm our proposition that a more effective visual perception system can advance the performance of cloth manipulation.

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Classification of clothing using interactive perception

Cited by 85 publications

References 25 publications

Occlusion-aware reconstruction and manipulation of 3D articulated objects

Occlusion-aware reconstruction and manipulation of 3D articulated objects

Bottom Dressing by a Dual-Arm Robot Using a Clothing State Estimation Based on Dynamic Shape Changes

A Precise Method for Cloth Configuration Parsing Applied to Single-Arm Flattening

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