Critic-observer-based decentralized force/position approximate optimal control for modular and reconfigurable manipulators with uncertain environmental constraints

A critic-observer decentralized force/position approximate optimal control method is presented to address the joint trajectory and contacted force tracking problem of modular and reconfigurable manipulators (MRMs) with uncertain environmental constraints. The dynamic model of the MRM systems is formulated as an integration of joint subsystems via extensive state observer (ESO) associated with the effect of interconnected dynamic coupling (IDC). A radial basis function neural network (RBF-NN) is developed to deal with the IDC effects among the independent joint subsystems. Based on adaptive dynamic programming (ADP) approach and policy iteration (PI) algorithm, the Hamilton–Jacobi–Bellman (HJB) equation is approximately solved by establishing critic NN structure and then the approximated optimal control policy can be derived. The closed-loop manipulator system is proved to be asymptotic stable by using the Lyapunov theory. Finally, simulation results are provided to demonstrate the effectiveness and advantages of the proposed control method.

Optimal Architecture Planning of Modules for Reconfigurable Manipulators

SUMMARY Modules are requisite for the realization of modular reconfigurable manipulators. The design of modules in literature mainly revolves around geometric aspects and features such as lengths, connectivity and adaptivity. Optimizing and designing the modules based on dynamic performance is considered as a challenge here. The present paper introduces an Architecture-Prominent-Sectioning (APS) strategy for the planning of architecture of modules such that a reconfigurable manipulator possesses minimal joint torques during its operations. Proposed here is the transferring of complete structure into an equivalent system, perform optimization and map the resulting arrangement into possible architecture. The strategy has been applied on a set of modular configurations considering three-primitive-paths. The possibility of getting advanced/complex shapes is also discussed to incorporate the idea of a modular library.

An Optimal Architectural Design for Unconventional Modular Reconfigurable Manipulation System

Modular and Reconfigurable manipulators have gained popularity especially in the service sector, where the use of customized configurations has increased. Adaptable modular designs have come into advances in achieving the required configuration of a robotic manipulator. As reported in the literature, various designs of the modules mainly with conventional configurations are presented and a few are reported with unconventional adjustments. To cater the non-repetitive applications, this paper presents an optimal architectural design for unconventional parameters for customized reconfigurability. This lighter and easier to connect version is also applicable to n-DoF and unconventional robotic parameters. Architecture Prominent Sectioning (APS) strategy is proposed which assumes an architecture as a set of point masses and optimally relocate components with respect to the minimization of the joint torques. Modules are considered to be 3-D printables using poly-lactic acid (PLA), a thermoplastic material, and thus light in weight. The new modular architecture design is validated through the assemblage of conventional/unconventional configurations using two types of modules namely Heavy(H) and Light(L). Along with that, worst torque analysis for the different configurations has been done in order to provide a strategy for assembly combinations. A comparative study is presented based upon the payload to the manipulator weight ratio, involving other reported architectures.