Teleoperation and robotic manipulation research from NASA played a key role in the early development of underwater remotely operated vehicles. NASA tackled controlling robots in dangerous, hard-to-reach environments, which led to robust control systems, tethered operation, depth-rated housings, and effective sensor and camera setups. Those technologies and design approaches were directly applied to underwater exploration and maintenance, so many of the first practical ROVs drew from NASA-built concepts and hardware. Other organizations, like the Navy and universities, contributed as well, but NASA’s work provided a strong engineering foundation that helps explain why this statement is true.

Proximity sensors are designed to detect whether something is nearby within a fixed range. They typically output a simple signal indicating “object present” or not, or sometimes give a distance to the nearest object. They’re not built to count how many objects are in the air at once. Counting requires resolving and distinguishing multiple targets, which is beyond the standard capability of a single proximity sensor. For counting, you’d use a system like a camera with vision processing or a radar/LiDAR setup, or an array of sensors that can track multiple objects. So the statement is false.

Incremental control relies on discrete inputs to advance motion in small steps. Pushbuttons and keypads fit this role because each press can be mapped to a fixed, predefined amount of movement for a robot joint or axis. This allows a human operator to nudge the robot precisely, step by step, which is exactly how jog modes and teach pendants are used in practice. If you want a tiny adjustment, press once; for another tiny adjustment, press again. Some systems may let a held input produce continuous motion or alter the step size, but the core idea remains that these devices enable controlled, incremental movement rather than a single seamless velocity. So the statement is true: pushbuttons and keypads can be used for incremental control of robot motion.

Feedback in closed-loop control relies on sensing the actual output, comparing it to the desired value, and adjusting the actuator to correct any deviation. When disturbances push the system away from its target, the sensor detects the change, and the controller applies a corrective action to bring the output back toward the setpoint. This ongoing adjustment makes the system more robust to disturbances because it actively counteracts their effect rather than leaving the output to drift. Statements that claim closed-loop control is the simplest form, that it doesn’t use sensors, or that it cannot handle disturbances aren’t accurate. Closed-loop control uses sensors and feedback, and its main advantage is its ability to reject disturbances through those continuous corrections.