SwarmCom: an infra-red-based mobile ad-hoc network for severely constrained robots

Abstract

Swarm robotics investigates groups of relatively simple robots that use decentralized control to achieve a common goal. While the robots of many swarm systems communicate via optical links, the underlying channels and their impact on swarm performance are poorly understood. This paper models the optical channel of a widely used robotic platform, the e-puck. It proposes SwarmCom, a mobile ad-hoc network for mobile robots. SwarmCom has a detector that, with the help of the channel model, was designed to adapt to the environment and nearby robots. Experiments with groups of up to 30 physical e-pucks show that (i) SwarmCom outperforms the state-of-the-art infra-red communication software-libIrcom-in range (up to 3 times further), bit error rate (between 50 and 63% lower), or throughput (up to 8 times higher) and that (ii) the maximum number of communication channels per robot is relatively low, which limits the load per robot even for high-density swarms. Using channel coding, the bit error rate can be further reduced at the expense of throughput. SwarmCom could have profound implications for swarm robotics, contributing to system understanding and reproducibility, while paving the way for novel applications. Keywords Swarm robotics • MANET • Infra-red communication • Channel model • e-puck • libIrcom S.M. Trenkwalder is a recipient of a DOC Fellowship of the Austrian Academy of Sciences. This is one of the several papers published in Autonomous Robots comprising Special Issue on Robot Communication Challenges: Real-World Problems, Systems, and Methods.

Proposed Different Signal Processing Tools for Efficient Optical Wireless Communications

“…At the receiver, the photodetector generates the photocurrent Y (t). The mathematical expression that describes the IM/DD system model is defined by [22]:…”

“…The ceiling bounce model is the most used model for simulating the impulse response of the indoor OWC channel. It was proposed by Trenkwalder et al [22]. Two parameters can characterize the ceiling bounce model: the Root Mean Square Delay Spread (D RMS ) and the optical path loss as given in Eqs.…”

“…x ADO (t) = x ACO (t) + x DCO (t) (22) The proposed ADO-OFDM is the same as the ADO-OFDM except for the decoding process. At the end of the proposed ADO-OFDM receiver, the received ADO-OFDM signal is demodulated and decoded.…”

Morphological communication for swarms

“…In robotic swarms, this communication is typically implemented using wireless technologies, for example WiFi (Hauert et al, 2010), Zigbee (Cianci et al, 2006), or other radio based technologies (Li et al, 2009b;Tutuko and Nurmaini, 2014). While other systems have been proposed using light (Rubenstein et al, 2014;Roberts et al, 2009;Trenkwalder et al, 2020), or sensory readings such as vision (Floreano et al, 2007;Garattoni and Birattari, 2018).…”