Abstract
Space modular self-reconfigurable satellites (SMSRSs) are a new type of satellite with reconfigurable structures and adjustable functions. The inverse kinematics of the hyper-redundant structure of SMSRSs are difficult to solve by traditional methods. In this paper, the inverse kinematics of SMSRS is transformed into an optimization problem and solved using the optimization method. Moreover, the avoidance of self-collision is implemented in the optimization process. Firstly, the kinematic model of SMSRS is established. Then, to find the more accurate inverse kinematics solutions, a novel Segmented Hybrid CMA-ES and PSO (SHCP) algorithm is proposed. The algorithm is used for three cases of inverse kinematic problems, and the optimization results prove the optimization method is effective to solve the inverse kinematic problem with self-collision avoidance. Compared to the results of PSO variants, meta-heuristic algorithms, and hybrid algorithms, the novel algorithm has higher accuracy, proving its better performance on the inverse kinematics problem of SMSRS.
Highlights
Optimization algorithm (PSO) [14,15], the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) [16] and the Differential Evolution algorithm (DE) [17,18], et al In inverse kinematics of space modular self-reconfigurable satellites (SMSRSs), different from other self-reconfiguration systems, the SMSRS is concerned with the pose of multiple modules and the pose of the end-effector
We investigate how to use the optimization method to solve the inverse kinematics of hyper-redundant SMSRSs and propose the Segmented Hybrid CMA-ES and PSO (SHCP) algorithm, which makes use of the global search advantages of PSO optimization and the local search advantages of CMA-ES algorithms by adopting the segmented hybrid concept to improve the algorithm performance
Compared with some PSO variants, hybrid algorithms, and meta-heuristic algorithms, SHCP has great advantages in general and can find higher quality solutions for desired poses of task modules, which proves the SHCP algorithm is adaptable for the inverse kinematics of SMSRSs
Summary
The structure of conventional spacecraft is usually permanently fixed to perform a single task and cannot be reconfigured for other tasks. The SMSRS should be converted from the current configuration to target configuration by joint rotations, where a key aspect is to calculate the angle of rotation required of each joint It involves converting the desired module poses of the SMSRS in Cartesian space to the joint angles in joint space, known as the inverse kinematics problem. Optimization algorithm (PSO) [14,15], the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) [16] and the Differential Evolution algorithm (DE) [17,18], et al. In inverse kinematics of SMSRS, different from other self-reconfiguration systems (e.g., space manipulators), the SMSRS is concerned with the pose of multiple modules and the pose of the end-effector.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
