Indoor robot gardening: design and implementation

• Main Authors: Correll, Nikolaus (Author), Arechiga, Nikos (Contributor), Bolger, Adrienne M. (Contributor), Bollini, Mario A. (Contributor), Charrow, Ben (Contributor), Clayton, Adam (Contributor), Dominguez, Felipe A. (Contributor), Donahue, Kenneth M. (Contributor), Dyar, Samuel S. (Contributor), Johnson, Luke B. (Author), Liu, Huan (Contributor), Patrikalakis, Alexander (Contributor), Robertson, Timothy (Contributor), Smith, Jeremy (Contributor), Soltero, Daniel Eduardo (Contributor), Tanner, Melissa (Contributor), White, Lauren L. (Contributor), Rus, Daniela L. (Contributor)
• Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Rus, Daniela (Contributor), Johnson, Luke (Contributor)
• Format: Article
• Language: English
• Published: Springer-Verlag, 2012-07-18T21:05:36Z.
• Subjects: Article
• Online Access: Get fulltext

 This paper describes the architecture and implementation of a distributed autonomous gardening system with applications in urban/indoor precision agriculture. The garden is a mesh network of robots and plants. The gardening robots are mobile manipulators with an eye-in-hand camera. They are capable of locating plants in the garden, watering them, and locating and grasping fruit. The plants are potted cherry tomatoes enhanced with sensors and computation to monitor their well-being (e.g. soil humidity, state of fruits) and with networking to communicate servicing requests to the robots. By embedding sensing, computation, and communication into the pots, task allocation in the system is de-centrally coordinated, which makes the system scalable and robust against the failure of a centralized agent. We describe the architecture of this system and present experimental results for navigation, object recognition, and manipulation as well as challenges that lie ahead toward autonomous precision agriculture with multi-robot teams.