A dynamically reconfigurable underwater robot, which can vary its configuration during a mission, would be useful for confined environment exploration and docking because of its versatility. A mission can be performed by choosing among different configurations, and the energy cost may increase, owing to the reconfigurability of the robot. Energy saving is the critical issue in long-range missions with underwater robots. Moreover, control allocation must be considered for a redundant system and input constraints. We propose an approach for an energy-efficient configuration and control allocation for a dynamically reconfigurable underwater robot that is built for karst exploration. The proposed method is based on sequential quadratic programming, which minimizes an energy-like criterion with respect to robotic constraints, i.e., mechanical limitations, actuator saturations, and a dead zone. The optimization problem is solved in each sampling instant. Two popular tasks for underwater robots, i.e., path-following and station-keeping (observation) problems, are simulated, and the simulation results show the efficiency of the method. Moreover, an experiment is carried out to highlight the results.