A data grid strategy for non-prehensile object transport by a multi-robot system

Abstract

The field of cooperative object transport within swarm and multi-robot systems (MRS) is an interesting area of research because exploring the dynamics of how multiple robots collaborate to transport objects presents fascinating opportunities to advance the capabilities of robotic teams. In this thesis we propose a control framework for non-prehensile object transport using a multi-robot system. While an object can be unmanageable for a single robot to push and transport, we demonstrate via simulations that a team of cooperative robots can be used to transport such an object. The proposed control strategy is divided into two phases: caging and cooperative transport. In the first phase, the robots start from arbitrary positions and then approach the object to be transported, forming a cage around it. The second phase consists of cooperatively transporting the object ensuring that it remains caged during transport. In the proposed strategy, the robots take a decentralized approach, wherein each robot operates autonomously while maintaining indirect communication with other robots. This is achieved by utilizing distributed data structures, such as distributed locks, sets, and maps, offered by the concept of an in-memory data grid (IMDG). By leveraging these distributed data structures, the robots can effectively share their respective states with one another. The key advantage of employing distributed data structures within our strategy is that it eliminates the need to develop a new application-specific protocol for interrobot communication. Instead, we can take advantage of the existing functionality provided by the data grid, which offers a convenient mechanism for exchanging information between robots. To our knowledge, the utilization of an IMDG in the domain of MRS is a novel concept. This thesis introduces a proposed design for a coordinated motion control strategy specifically aimed at object transport. The strategy leverages the capabilities of an IMDG, and presents it as a promising framework to simplify the communication process among the robots involved, leading to improved coordination and optimized object transport operations. We showcase the results of our research using a realistic simulator that effectively illustrates the viability of our method. This demonstration helps validate the effectiveness and potential of our methodology in various environments.