Ex Silico:Soft Biomorphs
Notice bibliographique
Résumé
Human existence is deeply enmeshed with the natural environment, and humans possess an innate connection with living beings and natural elements. Within art, design, and architecture, this is reflected in the transhistorical concept of biomorphism, which refers to a preference for or an interest in organic, lifelike forms that are evocative of nature and natural organisms. This zoom.able disseminates research towards envisioning soft biomorphism as an alternative design paradigm for soft robotics (robots made from pliable and elastic materials). Earlier work on soft robotics has mainly been anchored in technical science and focused on improving the abilities of robots through mimicking the physiology and mechanical operations of soft natural organisms. Soft biomorphism seeks to enact a different perspective, to facilitate a reorientation of the field’s interests. The notion of soft biomorphism is based on the simple premise of interrogating what happens when the inherently organic aesthetic of soft robots is emphasized and enhanced by incorporating inspiration from forms, colors, textures, and patterns of a biological origin. Soft biomorphism differs from other bioinspired design approaches used in robotics, as it eschews exact replication of a particular organism’s morphological features, instead favoring select idiosyncratic or general visual and haptic similarities with natural organisms. Rather than seeking to deceive users into believing that a robot is alive, biomorphic elements are incorporated to cultivate connection and empathy between humans and machines. By appearing lifelike, yet unfamiliar, soft biomorphic robot designs could facilitate more open-ended, negotiable human–robot relations that are not modeled on human–human interaction or interactions with specific animals or domesticated pets. The artistic motivations underlying soft biomorphism also include critically reflecting on the boundaries between nature, technology, and their cultural uses and meanings. This practice-based work unites approaches from our diverse disciplinary backgrounds within soft robotics, mechanical engineering, human–robot interaction, artistic practice, and design research. We initially sought to unpack and enact soft biomorphism through the construction of a series of material prototypes and actuated behavioral objects. The interaction potentials of these soft biomorphic prototypes were subsequently interrogated in a physical human–robot interaction study (Christiansen et al., 2023). This zoom.able focuses on articulating soft materiality and the biomorphological character of the prototypes as grounds for sensory perception, a potentiality of bodily sensations, and distinct types of embodied knowledge. While movement, sensing, and artificial cognition are integral to robotics technology and its aesthetics in general, our work investigates how soft materials themselves hold the potential to generate their own forms and relations when embedded in robotics. We further explore the aesthetics of soft biomorphic robots by employing photographs of our physical prototypes and text descriptions of their biomorphic inspirations as inputs for an AI image generation software. The resulting outputs, presented jointly on the final layer of the zoomable, suggest that connections in the web of life self-reflexively query the reification and remediation of biomorphic qualities within the virtual, latent space of global visual culture.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,039 | 0,008 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».