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In this chapter, we mainly focus on MINOS and Habitat since they provide more customization abilities (number of sensors, their positions, and their parameters) and are implemented in a loosely coupled manner to generalize well to new multisensory tasks and environments. As their API can be used to define any high‐level task and the material, object clutter variation and many more can be programmatically configured for the environment. They both support navigation with both continuous and discrete state spaces. Also, for the purpose of their benchmarks, all the actuators are noiseless, but they both have the ability to enable noises if desired [75].

In the last section, we saw numerous task definitions and how they each can be tackled by the agents. So, before jumping into MINOS and Habitat simulators and reviewing them, let us first get more familiarized with the three main goal‐directed navigation tasks, namely, PointGoal Navigation, ObjectGoal Navigation, and RoomGoal Navigation.

In PointGoal Navigation, an agent is appeared at a random starting position and orientation in a 3D environment and is asked to navigate to target coordinates that are given relative to the agent's position. The agent can access its position via an indoor GPS. There exists no ground‐truth map, and the agent must only use its sensors to do the task. The scenarios start the same for ObjectGoal Navigation and RoomGoal Navigation as well; however, instead of coordinates, the agent is asked to find an object or go to a specific room.