The multi-locomotion robot (MLR), including bionic insect microrobot, bionic animal robot and so on, should choose different locomotion modes according to the obstacles it faces. However, under different locomotion modes, the power consumption, moving speed, and falling risk of MLR are different, and in most cases, they are mutually exclusive. This paper proposes a path planning algorithm for MLR based on a multi-objective genetic algorithm with elitist strategy (MLRMOEGA), which has four optimization objectives: power consumption, time consumption, path falling risk, and path smoothness. We propose two operators: a map analysis operator and a population diversity expansion operator, to improve the global search ability of the algorithm and solve the problem so that it is easy to fall into the local optimal solution. We conduct simulations on MATLAB, and the results show that the proposed algorithm can effectively optimize the objective function value compared with the traditional genetic algorithm under the equal weight of the four optimization objectives, and, under alternative weights, the proposed algorithm can effectively generate the corresponding path of the decision maker’s intention under the weight of preference. Compared with the traditional genetic algorithm, the global search ability is improved effectively.

This article mainly introduces a dynamically stabilized and balanced point-footed bipedal robot, which we named MPLBR (Multi-locomotion Parallel-Legged Bipedal Robot). The robot structure is designed with a symmetric architecture, including six motors and a five-link double crank mechanism for extending the legs. Based on the inverted pendulum model, a robot control process framework is proposed using the virtual model control (VMC) algorithm and the decoupling balance control algorithm, combined with robot gait planning and state detection, to achieve stable walking and hopping control of the robot. Through simulation experiments and physical prototype experiments to verify the algorithm, the robot can achieve stable walking control and bounce motion modes.

This paper presents the design and control of a lightweight three degrees of freedom robotic arm based on a load-adaptive hoisting mechanism. The proposed design integrates a spring-loaded rope and a variable radius reel into the gripper, enabling efficient load adaptability with minimal structural complexity. By leveraging this mechanism, the robotic arm achieves significant weight reduction while maintaining robust performance under variable payloads. The study includes a comprehensive analysis of the system’s kinematics and dynamics, focusing on the interaction between the adaptive gripper and the arm structure. A prototype of the robotic arm was developed and experimentally tested to validate its functionality.

This paper introduces a planar positioning sensing system based on orthogonal wheels and encoders for some surfaces that may float (such as ship decks). The positioning sensing system can obtain the desired position and angle information on any such ground that floats. In view of the current method of using the IMU gyroscope for positioning, the odometer data on these floating grounds are not consistent with the real-time data in the world coordinate system. The system takes advantage of the characteristic of the orthogonal wheel, using four vertical omnidirectional wheels and encoders to position on the floating ground. We design a new structure and obtain the position and angle information of a mobile robot by solving the encoder installed on four sets of omnidirectional wheels. Each orthogonal wheel is provided with a sliding mechanism. This is a good solution to the problem of irregular motion of the system facing the floating grounds. In the experiment, it is found that under the condition that the parameters of the four omnidirectional wheels are obtained by the encoder, the influence of the angle change of the robot in the world coordinate system caused by the flotation of the ground can be ignored, and the position and pose of the robot on the fluctuating ground can be well obtained. Regardless of straight or curved motion, the error can reach the centimeter level. In the mobile floating platform experiment, the maximum error of irregular movement process is 2.43 (±0.075) cm and the RMSE is 1.51 cm.