From Rule-driven to Collective Intelligence Emergence:A Review of Research on Multi-robot Air-ground Collaboration
The multi-robot air-ground collaboration system,which is crucial for search and rescue,exploration,and other fields,has garnered significant attention from researchers in recent years.Overcoming challenges related to limited intelligence and weak autonomy in such systems is essential to enhance individual intelligence and strengthen collective collaboration autonomy,thereby accelerating their practical applications.In recent years,with the continuous advancement of artificial intelligence(AI)algorithms in perception and decision-making,such as deep learning and collective intelligence,their applications to air-ground collaborative systems have become a re-search hotspot.Based on the level of autonomy in air-ground collaboration,this paper summarizes air-ground col-laboration efforts at different collaboration levels,ranging from rule-driven approaches to collective intelligence emergence,emphasizing the enhancement of individual intelligence to achieve collective intelligence.Furthermore,this paper constructs the concepts and expands the features of the air-ground collaboration collective intelligence system,and outlines its self-organizing,self-adapt at ion,self-learning,and continuously evolving qualities.Finally,by listing representative application scenarios,this paper encapsulates the challenges and explores future directions in air-ground collaboration.
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维普
