To enable unmanned aerial vehicle (UAV) operators to efficiently and intuitively convey their commands to a swarm of UAVs, we propose the use of natural and human-centric input modalities, such as voices and gestures. This paper addresses the fusion of input modalities such as voice and gesture data, which are captured through a microphone and a Leap Motion controller, respectively, to control UAV swarms. The obtained experimental results are presented, and the achieved performance (accuracy) is analyzed. Finally, combined human factor ergonomics test with a questionnaire to verify the method’s validity.

The cooperation of multiple unmanned aerial vehicles (Multi-UAV) can effectively solve the area coverage problem. However, developing an online multi-UAV coverage approach remains a challenge due to energy constraints and environmental dynamics. In this paper, we design a comprehensive framework for area coverage with multiple energy-limited UAVs in dynamic environments, which we call MCTA (Multi-UAV Coverage through Two-step Auction). Specifically, the online two-step auction mechanism is proposed to select the optimal action. Then, an obstacle avoidance mechanism is designed by defining several heuristic rules. After that, considering energy constraints, we develop the reverse auction mechanism to balance workload between multiple UAVs. Comprehensive experiments demonstrate that MCTA can achieve a high coverage rate while ensuring a low repeated coverage rate and average step deviation in most circumstances.