Abstract:We explore transdisciplinary collaborations between artists and roboticists across a portfolio of artworks. Brendan Walker's Broncomatic was a breath controlled mechanical rodeo bull ride. Blast Theory's Cat Royale deployed a robot arm to play with a family of three cats for twelve days. Different Bodies is a prototype improvised dance performance in which dancers with disabilities physically manipulate two mirrored robot arms. We reflect on these to explore how artists shape robotics research through the two key strategies of improvisation and provocation. Artists are skilled at improvising extended robot experiences that surface opportunities for technology-focused design, but which also require researchers to improvise their research processes. Artists may provoke audiences into reflecting on the societal implications of robots, but at the same time challenge the established techno-centric concepts, methods and underlying epistemology of robotics research.
Abstract:We report on a three-day challenge during which five teams each programmed a nanodrone to be piloted through an obstacle course using bodily movement, in a 3D transposition of the '80s video-game Pacman. Using a bricolage approach to analyse interviews, field notes, video recordings, and inspection of each team's code revealed how participants were shaping and, in turn, became shaped in bodily ways by the drones' limitations. We observed how teams adapted to compete by: 1) shifting from aiming for seamless human-drone interaction, to seeing drones as fragile, wilful, and prone to crashes; 2) engaging with intimate, bodily interactions to more precisely understand, probe, and delimit each drone's capabilities; 3) adopting different strategies, emphasising either training the drone or training the pilot. We contribute with an empirical, somaesthetically focused account of current challenges in HDI and call for programming environments that support action-feedback loops for design and programming purposes.
Abstract:C\^ote d'Ivoire and Ghana, the world's largest producers of cocoa, account for two thirds of the global cocoa production. In both countries, cocoa is the primary perennial crop, providing income to almost two million farmers. Yet precise maps of cocoa planted area are missing, hindering accurate quantification of expansion in protected areas, production and yields, and limiting information available for improved sustainability governance. Here, we combine cocoa plantation data with publicly available satellite imagery in a deep learning framework and create high-resolution maps of cocoa plantations for both countries, validated in situ. Our results suggest that cocoa cultivation is an underlying driver of over 37% and 13% of forest loss in protected areas in C\^ote d'Ivoire and Ghana, respectively, and that official reports substantially underestimate the planted area, up to 40% in Ghana. These maps serve as a crucial building block to advance understanding of conservation and economic development in cocoa producing regions.