28 research outputs found
A Robot to Shape your Natural Plant: The Machine Learning Approach to Model and Control Bio-Hybrid Systems
Bio-hybrid systems---close couplings of natural organisms with
technology---are high potential and still underexplored. In existing work,
robots have mostly influenced group behaviors of animals. We explore the
possibilities of mixing robots with natural plants, merging useful attributes.
Significant synergies arise by combining the plants' ability to efficiently
produce shaped material and the robots' ability to extend sensing and
decision-making behaviors. However, programming robots to control plant motion
and shape requires good knowledge of complex plant behaviors. Therefore, we use
machine learning to create a holistic plant model and evolve robot controllers.
As a benchmark task we choose obstacle avoidance. We use computer vision to
construct a model of plant stem stiffening and motion dynamics by training an
LSTM network. The LSTM network acts as a forward model predicting change in the
plant, driving the evolution of neural network robot controllers. The evolved
controllers augment the plants' natural light-finding and tissue-stiffening
behaviors to avoid obstacles and grow desired shapes. We successfully verify
the robot controllers and bio-hybrid behavior in reality, with a physical setup
and actual plants
Flora robotica -- An Architectural System Combining Living Natural Plants and Distributed Robots
Key to our project flora robotica is the idea of creating a bio-hybrid system
of tightly coupled natural plants and distributed robots to grow architectural
artifacts and spaces. Our motivation with this ground research project is to
lay a principled foundation towards the design and implementation of living
architectural systems that provide functionalities beyond those of orthodox
building practice, such as self-repair, material accumulation and
self-organization. Plants and robots work together to create a living organism
that is inhabited by human beings. User-defined design objectives help to steer
the directional growth of the plants, but also the system's interactions with
its inhabitants determine locations where growth is prohibited or desired
(e.g., partitions, windows, occupiable space). We report our plant species
selection process and aspects of living architecture. A leitmotif of our
project is the rich concept of braiding: braids are produced by robots from
continuous material and serve as both scaffolds and initial architectural
artifacts before plants take over and grow the desired architecture. We use
light and hormones as attraction stimuli and far-red light as repelling
stimulus to influence the plants. Applied sensors range from simple proximity
sensing to detect the presence of plants to sophisticated sensing technology,
such as electrophysiology and measurements of sap flow. We conclude by
discussing our anticipated final demonstrator that integrates key features of
flora robotica, such as the continuous growth process of architectural
artifacts and self-repair of living architecture.Comment: 16 pages, 12 figure