Active Perception within BDI Agents Reasoning Cycle

In multi-agent systems the main process responsible for obtaining information about the environment is perception, generally this process is performed passively regardless the agent's intentional state. However, especially when inserted in the real world, a frequent problem is that agents have partial perception of the environment, failing to perceive some relevant information. To circumvent this problem, a solution is to actively take actions to perceive what is of interest to the agent, for example, in a computer vision system, the camera can be repositioned to have a better view of an object. This work aims to develop an active perception model integrated with the reasoning cycle of BDI agents. Experiments are performed using BDI agents with ROS to command unmanned aerial vehicles to analyze the benefits and impacts of using cognitive agents with active perception to program robot intelligence.