This study consists of two parts, and the first part is the Cable-driven boat motion simulator. In naval operations, vertical take-off and landing (VTOL) drones are widely used as cost-effective assets that are easy to maneuver, enhancing the reconnaissance and surveillance capabilities of ships. Despite their advantages, these drones have limited operational time and need to return to the base platform. To address the challenge of developing drone landing systems, conducting experiments at sea poses significant costs and risks. This dissertation proposes the utilization of a ground-based motion simulator that mimics the 6-DOF motion of a boat. The simulator aims to replicate the sea environment up to sea state 6 on the Doublas scale. To achieve motion control and optimization of the cable-driven boat motion simulator, a Control Lyapunov function-based Quadratic Program (CLF-QP) control method was studied. Given the importance of cable tension in cable-driven robots, the CLF-QP control method facilitates platform movement in the desired 6-DOF motions while ensuring that cable tensions remain within specified limits. In addition to the investigation into designing a boat motion simulator, a related research project focused on camera image-based pose estimation for drone landing. This study is preliminary research on drone landing control and specifically addresses the 3D rotation estimation of a moving platform using 2D images captured by a camera. The research assumes the presence of a circular pattern marker on the flight deck of a ship, with the drone hovering at the center of the platform. Equipped with a camera, the drone captures 2D imagesof the markers and measures the distance between them. As the platform rotates, the circular pattern of markers transforms into an ellipse. The study derives the ellipse equation from the marker positions on the ellipse, utilizing geometry and trigonometric functions to determine the platform’s rotation sequence. By estimating the platform’s rotation, the drone can effectively determine the optimal timing for the platform to rotate within the drone’s capacity to land safely. The proposed method was validated through simulation and hardware testing, with a subsequent discussion on the platform state, and tension tracking errors obtained by a motion capture system and load-cell tension sensors. The second part of this study is the Pipeline exploration and inspection robot. The research introduces a new robot design specifically tailored for inspecting, exploring, and mapping intricate pipe networks featuring multiple curves and joints. The proposed robot, named Model S4, stands out for its simplicity, high maneuverability, and static stability, achieved through the incorporation of four omniwheels arranged in a single plane at the robot center. The robot is equipped with high-torque motors that effectively control roll motions. The robot employs a spring-servo motor integrated series elastic actuator to enhance stability. This mechanism ensures that the robot maintains three or more points of contact with the opposite sidewalls of the pipe, causing the robot’s center plane to consistently align with the centerline of the pipe throughout its operation. This design promotes stable travel within the pipe at any orientation relative to gravity, without the need for constant feedback. Additionally, the robot features mechanisms designed for efficient navigation through pipe curves and T-joints, a capability validated through hardware testing focusing on roll control and maneuvering through pipe curves and joints. The primary contributions of this dissertation are as follows: 1. Control Lyapunov Function-based Quadratic Program (CLF-QP) control for motion control and tension optimization of the cable-driven boat motion simulator. 2. The workspace Analysis for Parameter Optimization of the cable-driven boat motion simulator utilizing static analysis, cable-to-cable and cable-to-platform interference detection algorithm. 3. Hardware model building and testing to verify the performance of CLF-QP control with the discussion of platform pose and tension tracking errors measured by a motion capture system and tension sensors. 4. The simulation and hardware experimental validation of a camera image-based platform rotation estimation. 5. A novel design of a robot for interior exploration and inspection of pipe networks embedding the torsion spring and servo motor integrated series elastic actuator.