Affordance

Summary

In psychology, affordance is what the environment offers the individual. In design, affordance has a narrower meaning, it refers to possible actions that an actor can readily perceive. American psychologist James J. Gibson coined the term in his 1966 book, The Senses Considered as Perceptual Systems, and it occurs in many of his earlier essays. His best-known definition is from his 1979 book, The Ecological Approach to Visual Perception:The affordances of the environment are what it offers the animal, what it provides or furnishes, either for good or ill. ... It implies the complementarity of the animal and the environment. The word is used in a variety of fields: perceptual psychology, cognitive psychology, environmental psychology, criminology, industrial design, human–computer interaction (HCI), interaction design, user-centered design, communication studies, instructional design, science, technology and society (STS), sports science and artificial intelligence. Origina

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Appropriation of a representational tool in a second-language classroom

Yun Wen

While the affordances of face-to-face and online environments have been studied somewhat extensively, there is relatively less research on how technology-mediated learning takes place across multiple media in the networked classroom environment where face-to-face and online interactions are intertwined, especially in the context of language learning. This case study contextually investigates the appropriation of a representational tool by students in small groups, in the context of collaborative second language writing activities. In this paper, micro-analysis of cross-media interactions is deployed to unravel how different groups of students evolve alternative approaches to appropriating the technology. The study explores the beneficial affordances of a representational tool that supplement face-to-face communication for second language learning, and draws implications for the design of collaborative L2 learning in networked classrooms.

Springer2015

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The existing tools for testing spam filters evaluate a filter instance by simply feeding it with a stream of emails, possibly also providing a feedback to the filter about the correctness of the detection. In such a scenario the evaluated filter is disconnected from the network of email servers, filters, and users, which makes the approach inappropriate for testing many of the filters that exploit some of the information about spam bulkiness, users' actions and social relations among the users. Corresponding evaluation results might be wrong, because the information that is normally used by the filter is missing, incomplete or inappropriate. In this paper we present a tool for testing spam filters in a very realistic scenario. Our tool consists of a set of Python scripts for unix/linux environment. The tool takes as inputs the filter to be tested and an affordable set of interconnected machines (e.g., PlanetLab machines, or locally created virtual machines). When started from a central place, the tool uses the provided machines to build a network of real email servers, installs instances of the filter, deploys and runs simulated email users and spammers, and computes the detection results statistic. Email servers are implemented using Postfix, a standard linux email server. Only per-email-server filters are currently supported, whereas per-email-client filters testing would require additional tool development. The size of the created emailing network is constrained only by the number of available PlanetLab or virtual machines. The run time is much shorter then the simulated system time, due to a time scaling mechanism. Testing a new filter is as simple as installing one copy of it in a real emailing network, which unifies the jobs of a new filter development, testing and prototyping. As a usage example, we test the SpamAssassin filter.

2007

From surgery to watchmaking, fine-manipulation skills highly rely on the dexterity afforded by both hands. Coordination is key to human dexterity. Specifically, humans need not only to govern the abundant intrinsic degrees of freedom (DOFs) to allocate controls of task-demanded variables, but also to adapt postures in response to extrinsic task conditions. In spite of the recent advances in robotics research, human dexterity remains unattainable for robots, especially in terms of flexibility and adaptability. Therefore, it is necessary to gain insights into human fine-manipulation skills, to advance the dexterity of robots in similar tasks. This thesis deepens our understanding of human dexterity by investigating the human coordination in fine-manipulation skills taken from watchmaking craftsmanship.The first part of this thesis investigates both intrinsic and extrinsic coordination of upper-limbs in a non-symmetrical and non-rhythmic bimanual fine-manipulation task. We conduct a comparative study in the assembly of a spring on the watch face. Analysis of motion kinematics reveals that professional subjects mitigate the task challenge by actively modifying task conditions. Moreover, we offer a novel perspective to understand the skill acquisition in humans. We hypothesize that the evolution of coordination during skill improvement is driven by the changes in the structure of the optimal criterion of the central nervous system. We employ a bi-level optimization framework to infer the structure of this optimal criterion.The second part investigates how roles and control variables are distributed across hands and fingers. We compare task performance of human subjects under two experimental conditions when dismounting a screw from a watch face. When the watch face needed positioning, the role distribution of both hands was strongly influenced by hand dominance; when the watch face was stationary, a variety of hand pose combinations emerged. We propose a taxonomy of bimanual hand pose combinations and develop a graphical matrix-based representation approach to afford analysis of experimental observations. Our analysis suggests that the control of independent task demands is distributed across either hands or functional groups of fingers.In the third part, we take inspiration from human coordination principle to advance the dexterity of a robotic hand by exploiting its redundant DOFs. We propose a human-like algorithm to enable a robotic hand to grasp objects using arbitrary surface regions, no longer restricted to regular grasp types, such as pinch or power grasp. We present an iterative process to empower the robotic hand to grasp multiple objects in sequence. Moreover, we formulate a strategy to facilitate the exploitation of redundant DOFs for multitask planning. Our approaches have been validated both in simulation and on a real robotic hand.In summary, this thesis not only offers a deeper understanding of human dexterity by revealing both the intrinsic and extrinsic coordination of upper-limbs and the role distribution across hands in bimanual fine-manipulation tasks, but also proposes algorithms that enable multi-fingered robotic hands to achieve human-like dexterous grasping of a single or even multiple objects using arbitrary surface regions. This thesis offers the prospect of developing algorithms for robotic dexterous grasping and manipulation, and also inspires the design of novel robotic hands and manipulators.

EPFL2022

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EPFL2022