Optimal motion planning of juggling by 3-DOF manipulators using adaptive PSO algorithm

Abstract

Three-DOF manipulators were employed for juggling of polygonal objects in order to have full control over object's configuration. Dynamic grasp condition is obtained for the instances that the manipulators carry the object on their palms. Manipulation problem is modeled as a nonlinear optimal control problem. In this optimal control problem, time of free flight is used as a free parameter to determine throw and catch times. Cost function is selected to get maximum covered horizontal distance using minimum energy. By selecting third-order polynomials for joint motions, the problem is changed to a constrained parameter selection problem. Adaptive particle swarm optimization method is consequently employed to solve the optimization problem. Effectiveness of the optimization algorithm is verified by a set of simulations in MSC. ADAMS.

Modeling, analysis and control of robot–object nonsmooth underactuated Lagrangian systems: A tutorial overview and perspectives

“…Future robotics is likely to require highly complex tasks: bipedal machines which walk/run/jump/crawl and more [134,135,136,119], quadruped robots which walk/run/gallop/trot/amble/bound/pace/half bound/transversally gallop/kick/jump on their rear legs, robots which grasp/dexterously manipulate/push/tap/juggle [137,138,9], robots which throw/catch [139,140], which climb/slide along poles, quadropters which juggle/catch/throw a ball [141,142], manipulation with mobile manipulator for timber harvesting tasks [143], etc. In all cases the contact points should be allowed to stick or/and to slip [144], which is unavoidable as it is shown on simple examples in [118].…”

“…Assume now that the objective is to catch the moving object, with a nonzero restitution coefficient (in (26) the index set α(t) switches once from ∅ to {1}). The objective is to catch the object at a desired height q 1,d and at a desired time instant t cat , and to keep the contact for all t ≥ t cat (hence for all t > t cat the task is as in section 3.1.2), or on some finite time-interval for toss juggling tasks [149,140]. If e n > 0 the catching implies that q1 (t…”

“…The principle is to track the object's motion and to design a mirror-like motion of the object's motion for the robot, and regulating the object at impacts. Similarly to the OGY method, this seems to mainly apply to juggling systems which satisfy M 2 (q) ≫ M 1 (q) (hence q2 remains continuous at impacts, an assumption that is widely spread in juggling systems analysis [334,159,257,59,158,216,141,335,70,275,327,140]). The dead-beat controller designed in [13,14] is shown to reduce to a mirror algorithm when this assumption holds.…”

A New Mechanism for Passive Dynamic Object Manipulation along a Curved Path

“…Grasp-less manipulation approach has some advantages and some disadvantages over manipulation with grasp. Advantages of grasp-less manipulation include minimalism in mechanism [25], reduction in cost [26], opportunity of transferring object out of robot's workspace [19], [20], elimination of need for compliance control and finger coordination in establishing stable grasp, possibility of doing tasks with more DoF (Degrees of Freedom) than the DoF of the robot [27] and exploiting geometry and dynamics of the environment in performing the manipulation [25]. When different tasks are not expected from the mechanism, manipulation task is not complicated and simplicity and cost are most important factors, grasp-less manipulation is preferred.…”

Nonholonomic motion planning for minimizing base disturbances of space manipulators based on multi-swarm PSO

“…Other methods have been proposed in previous works. 2,[14][15][16][17][18][19][20][21][22][23][24] In this paper, a planning method inspired by previous work is proposed to plan nonholonomic motion to minimize base disturbance for 6-DOF space manipulators. The paper is organized as follows: Section 2 derives the direct kinematic equations of the manipulator system.…”