Natural environments are always filled with bird flocks and animal herds, which are known as collective behaviors. In recent years, these behaviors have attracted the attention of many researchers. Inspired by such behavior, researchers have replicated it in robotic systems. However, most of them utilize centralized sensing technologies, such as GPS and VICON, which limit the range of operations of robot swarms. It is necessary to implement a fully distributed sensing and control system in order to overcome these drawbacks. No external infrastructure is needed to enable the robotic system to be operated both indoors and outdoors.

For the purpose of distributed sensing, only onboard sensors are selected. In order to accomplish this task, ultra-wideband (UWB) sensors and inertial measurem...[ Read more ]

Natural environments are always filled with bird flocks and animal herds, which are known as collective behaviors. In recent years, these behaviors have attracted the attention of many researchers. Inspired by such behavior, researchers have replicated it in robotic systems. However, most of them utilize centralized sensing technologies, such as GPS and VICON, which limit the range of operations of robot swarms. It is necessary to implement a fully distributed sensing and control system in order to overcome these drawbacks. No external infrastructure is needed to enable the robotic system to be operated both indoors and outdoors.

For the purpose of distributed sensing, only onboard sensors are selected. In order to accomplish this task, ultra-wideband (UWB) sensors and inertial measurement units (IMU) are selected, which can measure distance between sensors and provide pose information. Relative positioning and velocity estimation can be achieved by integrating these distance measurements. In addition, some flocking control systems are applied to achieve real-time control, such as the Vicsek model, Cucker-Smale model, and Cucker- Dong model.

This thesis investigates different sensing technologies and presents our reasoning for selecting UWB and IMU. After this, some relative localization algorithms and flocking models are also discussed. In addition, two relative localization algorithms are proposed in order to resolve relative positioning and velocity estimation in robotic systems. Based on these relative positioning algorithms, both simulation and experiments with several UGVs and quadruped robots are conducted. The work demonstrates a real autonomous robotic flock without the use of external devices, which demonstrates the feasibility of the proposed algorithms for relative localization and flocking models.