Abstract
Biological systems achieve amazing adaptive behavior with local agents performing simple sensing and actions. Modular robots with similar properties can potentially achieve self-adaptation tasks robustly. Inspired by this principle, we present a generalized distributed consensus framework for self-adaptation tasks in modular robotics. We demonstrate that a variety of modular robotic systems and tasks can be formulated within such a framework, including (1) an adaptive column that can adapt to external force, (2) a modular gripper that can manipulate fragile objects, and (3) a modular tetrahedral robot that can locomote towards a light source. We also show that control algorithms derived from this framework are provably correct. In real robot experiments, we demonstrate that such a control scheme is robust towards real world sensing and actuation noise. This framework can potentially be applied to a wide range of distributed robotics applications.
| Original language | English (US) |
|---|---|
| Article number | 5152663 |
| Pages (from-to) | 1881-1888 |
| Number of pages | 8 |
| Journal | Proceedings - IEEE International Conference on Robotics and Automation |
| DOIs | |
| State | Published - 2009 |
| Externally published | Yes |
| Event | 2009 IEEE International Conference on Robotics and Automation, ICRA '09 - Kobe, Japan Duration: May 12 2009 → May 17 2009 |
All Science Journal Classification (ASJC) codes
- Software
- Artificial Intelligence
- Electrical and Electronic Engineering
- Control and Systems Engineering