Motion and trajectory planning modeling for mobile landing mechanism systems based on improved genetic algorithm.

Area of Science:

• Robotics
• Aerospace Engineering
• Mechanical Engineering

Background:

• Traditional soft-landing missions separate landers and rovers, limiting functionality.
• Existing lander research primarily focuses on stationary platforms, neglecting mobile capabilities.
• The motion of legged mobile landers remains an understudied area.

Purpose of the Study:

• To propose and validate a novel Mobile Landing Mechanism (MLM).
• To develop and optimize a trajectory planning method for the MLM's joint space.
• To enhance the mobility and performance of spacecraft landing systems.

Main Methods:

• Monte Carlo simulation to determine mechanism workspace and verify motion feasibility.
• Cubic spline curve for joint space trajectory planning, considering velocity and acceleration constraints.
• Weighted coefficient method for optimal time-jerk pedestal trajectory planning.
• Comparative analysis of Genetic Algorithm (GA) and Adaptive Genetic Algorithm (AGA) for trajectory optimization.

Main Results:

• Workspace analysis confirmed the motion feasibility of the proposed MLM.
• Optimized joint trajectories were generated, ensuring continuous and stable motion.
• The adaptive genetic algorithm demonstrated superior performance in solving the joint trajectory optimization problem under constraints.

Conclusions:

• The proposed Mobile Landing Mechanism (MLM) is a rational and effective solution for enhancing spacecraft landing capabilities.
• The developed foot trajectory planning method ensures continuous, stable, and optimized motion.
• This research opens new avenues for mobile lander design and autonomous space exploration.