This paper aims to discuss the requirements of safe and smooth trajectory planning of transporter mobile robots to perform non-prehensile object manipulation task. In non-prehensile approach, the robot and the object must keep their grasp-less contact during manipulation task. To this end, dynamic grasp concept is employed for a box manipulation task and corresponding conditions are obtained and are represented as a bound on robot acceleration. A trajectory optimization problem is defined for general motion where dynamic grasp conditions are regarded as constraint on acceleration. The optimal trajectory planning for linear, circular and curve motions are discussed. Optimization problems for linear and circular trajectories were analytically solved by previous studies and here we focused with curve trajectory where Genetic Algorithm is employed as a solver tool. Motion simulations showed that the resulted trajectories satisfy the acceleration constraint as well as velocity boundary condition that is needed to accomplish non-prehensile box manipulation task. Manuscript profile

Trajectories generally used to describe the space and time required to perform a desired motion task for a mobile robot or manipulator system. In this paper, we considered a cubic polynomial trajectory for the problem of moving a mobile robot from its initial position to a goal position in over a continuous set of time. Along the path, the robot requires to observe a certain acceleration profile. Then, we formulated an optimization approach to generate optimal trajectory profiles for the mobile robot in the cases of maximum-distance and minimum-time problems. The optimization problem presented to find the trajectory strategy that would give the robot time-distance optimality to move from a start point to an end point where the robot should stay inside its acceleration limits all the time. The problem solved analytically because as it is well known, numerical solutions and iterative methods are time-consuming, therefore, our closed-form solutions demand low computation time. Finally, the results are verified by simulations. Manuscript profile