A comprehensive perspective on electric vehicles as evolutionary robots - Haoyang Che; Haoyang Che; Shaolin Wang; Shaolin Wang; Lei Yao; Ying Gu (Frontiers in Robotics and AI)
Multi-robot systems exhibit different application forms in human life, among these, electric vehicles (EVs) at rest and in motion can be perceived as a specialized category of multi-robot systems with increasingly sophisticated vehicle functions and a certain degree of flexibility, and most notably, the ability to iteratively evolve. However, for EVs to evolve into the next-generation of multi-robot systems, more complex technical and operational mechanisms shall be fully cultivated in EVs to develop their evolutionary capabilities, including, but not limited to multimodal environmental sensing techniques, advanced telematics communication protocols such as 5G, Over-The-Air (OTA) upgrade functions, real-time backend data lake analytics, and user-centric marketing initiatives. As it stands, these mechanisms are evidently insufficient for realizing genuine evolutionary robots (ER), especially in unstructured environments. The overarching perspective of conceptualizing EV as ER is not always prominently featured in academic literature. This manuscript provides a succinct overview of the ongoing transition from Software-Defined Vehicles (SDV) to Artificial Intelligence-Defined Vehicles (AIDV), and examines the ongoing research focused on the utilization of electric vehicles as mobile edge computing platforms. Furthermore, it discusses the fundamental evolutionary competencies that define modern electric vehicles, establishing the core tenets upon which our analysis is predicated. To transcend the status quo, we underscore the imperative and pressing need for profound transformations across a spectrum of pivotal domains within the field. Furthermore, this endeavor aims to amplify the reach and influence of research on EVs as ERs, potentially catalyzing the emergence of several niche research areas.