Deployed Coverage Search algorithms and Finite State Machine mechanism for an attic cleaning robot, accounting for various obstacle constraints and reduced overall task completion time by 30%.

• Developed a comprehensive and reliable solution that integrates a vision-based algorithm and advanced path-planning to facilitate dynamic movement in a walking robot equipped with an arm. This integration enables the robot to manipulate and transport objects with high precision and fluidity.

• Successfully implemented the RRT* algorithm, achieving a 30% reduction in computing resources compared to traditional methods. This enhancement also quadrupled the effective workspace of the robot's arm, significantly improving its operational range and efficiency.

• Applied PID control techniques to the quadruped's yaw and positional adjustments, ensuring stability and rapid convergence to target locations, thus maintaining the robot's equilibrium and performance under various conditions.

• Enhanced the localization capabilities of the quadruped by integrating a Kalman filter, which effectively minimized both process and measurement noise associated with Ultra Wide Bandwidth sensors. This adjustment increased the accuracy of localization by fourfold, surpassing the performance of standard configurations.

Our team create a practical approach to autonomous navigation for the vacuum cleaner,

leveraging the Model Predictive Control (MPC) framework. We have two success:

• Reformulated the spatial model to a Linear Time-Varying system model with the Taylor Expansion and Euler Discretization method so that our optimization contains time as a third state variable for optimization.

• Designed a recursive algorithm to keep tracking the time-varying maximum invariant set, which ensures the recursive feasibility of our MPC problem.

• Defined various constraints for the bicycle parking problem, formulated a mathematical model, constructed it as a QP problem, and successfully developed a strategy and an algorithm to minimize the overall parking cost(distance and time spent).