OCTOANTS: A Heterogeneous Lightweight Intelligent Multi-Robot Collaboration System with Resource-constrained IoT Devices

As the focus on highly intelligent robots continues, a problem that cannot be ignored has emerged: resource con-straints. Considering the game problem of resource limitation and the level of intelligence, we focus on lightweight intelligence. This work is a further refinement of our previous work, a heterogeneous lightweight intelligent multi-robot system. In-spired by the nature creatures “octopus” and “ants”. First, we propose a heterogeneous centralized-distributed architecture, which can make robots collaboration more flexible and non-redundant. Second, to reflect lightweight intelligence, we use the Raspberry Pi, a low computing and power consumption internet of things (IoT) device, as a processing platform and first propose a quantitative definition of the lightweight intelligent system. Then, combining the centralized-distributed architecture and the lightweight computing platform, we propose an adapted algorithm called OCTOANTS and apply it to the simultaneous localization and mapping (SLAM) field. The OCTOANTS architecture consists of one brain and eight tentacles, which can achieve complex things with proper collaboration between them. Finally, we use heterogeneous cameras and heterogeneous algorithms to form a lightweight intelligent collaborative system that can run in the real world. On the low-grade platform Raspberry Pi our heterogeneous tentacles frame rate can reach 41fps and 99.8fps respectively, power consumption is only 2W and 1.2W. At the same time, our heterogeneous system is on average 7.2% more accurate than the state-of-the-art homogeneous system and can be applied to a wider range of application scenarios, demonstrating the superiority and feasibility of our OCTOANTS.