In collaborative operations of multiple autonomous underwater vehicles (AUVs), the complexity of underwater environments and limited onboard energy make environmental adaptation and energy efficiency critical metrics for evaluating path quality. This paper addresses path conflict resolution in multi-AUV path planning by proposing an equal-time waypoint planning method. The approach involves randomly selecting equal-time waypoints in free space and generating path encoding sequences for each AUV. These path encodings are then optimized through four modules, considering both path smoothness and adaptability to ocean currents. The resulting paths comply with kinematic constraints while achieving reduced energy consumption. The method enables velocity adjustments across different segments to prevent conflicts. Simulation results demonstrate the feasibility of this approach in resolving multi-AUV path conflicts with low energy expenditure.

In order to improve the swimming performance of a paddle-propelled crablike robot, the sequence and parameters of swimming gait are planned according to the bionic swimming mechanism. Based on the bionic prototype of Portunus trituberculatus, the structure scheme of a leg–paddle hybrid driven robot is proposed with the functions of walking on land, crawling on seabed, and swimming underwater. By analyzing the underwater propulsion mechanism of single paddle and hydrodynamic performance of double paddles cooperatively propulsion, four direct swimming gaits are planned and the corresponding attitude changes are theoretically analyzed. Then, the numerical simulation and direct swimming experiments are carried out to verify the effectiveness of proposed gaits and correctness of force analysis. In alternate swimming gait of lift-based mode, the robot swims forward in a rolling attitude, with an advantage of the minimum water resistance and the optimum swimming velocity and efficiency. The influence of flapping frequency and relative phases of paddles on the swimming velocity shows the trend of raise first and then fall.

To achieve accurate 3D path tracking of a foot-wing hybrid-driven amphibious biomimetic robot under periodically varying forces, this study analyzes the periodic propulsion forces generated by the flapping motion of the robot’s feet and wings, along with the nonlinear hydrodynamic effects during underwater motion. To simplify the resulting complex force expressions, the scaling function averaging method is applied. Consequently, an accurate six-degree-of-freedom (6-DOF) dynamic model is established, in which the characteristic parameters of foot-wing flapping are adopted as control inputs. Based on this dynamic model, a nonlinear state-space representation of the robot’s underwater motion is constructed. In this formulation, 3D path tracking—derived from the Line-of-Sight (LOS) guidance method—and attitude stabilization are jointly defined as control objectives. To this end, a nonlinear model predictive control (NMPC) algorithm is employed to compute optimal control inputs, as it effectively addresses the challenges of strong nonlinearity, coupling effects, and multi-objective optimization. Finally, simulation experiments are conducted to validate the proposed control strategy. The results demonstrate that the robot is capable of accurately following the desired path. Furthermore, compared with conventional PID control, the NMPC approach significantly improves tracking stability and enhances the overall motion performance.