To browse Academia. We propose a general and simple method that handles free or point-to-point motion planning problem for redundant and non-redundant serial robots. The problem consists of linking two points in the operational space, under constraints on joint torques, jerks, accelerations, velocities and positions while minimizing a cost function involving significant physical parameters such as transfer time and joint torque quadratic average.
The basic idea is to dissociate the search of optimal transfer time T from that of optimal motion parameters. Inherent constraints are then easily translated to bounds on the value of T. Furthermore, a stochastic optimization method is used which not only may find a better approximation of the global optimal motion than is usually obtained via traditional techniques but that also handles more complicated problems such as those involving discontinuous friction efforts and obstacle avoidance.
This brief proposes a novel stochastic method that exploits the particular kinematics of mechanisms with redundant actuation and a well-known manipulability measure to track the desired end-effector task-space motion in an efficient manner. Whilst closed-form optimal solutions to maximise manipulability along a desired trajectory have been proposed in the literature, the solvers become unfeasible in the presence of obstacles.
A manageable alternative to functional motion planning is thus proposed that exploits the inherent characteristics of null-space configurations to construct a generic solution able to improve manipulability along a task-space trajectory in the presence of obstacles. The proposed Stochastic Constrained Optimization SCO solution remains close to optimal whilst exhibiting computational tractability, being an attractive proposition for implementation on real robots, as shown with results in challenging simulation scenarios, as well as with a real 7R Sawyer manipu In this paper, a trajectory planning method of a mobile manipulator is presented.
The problem is known to be complex in particular when dynamics is taken into account. Our approach is based on a simultaneous search for the robot path and the time evolution on this path. The whole problem is formulated in such a way that geometric and kinodynamic constraints are handled sequentially which makes more effective the use of a stochastic optimization technique.
