Manipulation at optimum locations for maximum force transmission with mobile robots under environmental disturbances

Abstract

Remote manipulation plays a key role for applications in hazardous conditions, yet designing a robust controller enabling safe interaction with unknown environment and under the influence of disturbances is a challenge. In this study, we propose effective control and optimization methods for mobile robotic manipulator systems that can increase effort transmission to a task in desired directions. The vehicle position is optimized by utilizing constrained particle swarm optimization where the objective is to enhance directional manipulability of the robotic arm within the system. A forward dynamic controller is implemented to eliminate undesired excessive motions near singular joint configurations. A reset control algorithm along with an admittance type controller are developed for stable interaction with an unknown object under environmental disturbances. The experimentally validated results show that the proposed method phase out undesired position disturbances and increase the directional manipulability for the required task enabling augmented effort transmission for the task execution.

Pose optimization for mobile manipulator grasping based on hybrid manipulability

“…For example, when conducting consecutive manipulation tasks, (Reister et al , 2022) combined the navigation cost of traversing all required positions and the manipulation cost together for the time-efficient placements of the mobile manipulator, and evaluated their method in both simulation and real-world scenarios. (Tugal et al , 2022) optimized the platform position subject to maximize the force transmission for remote manipulation tasks. When the operation mode is intermittent, (Ren et al , 2016) analyzed the mobile base’s workable area when the wrist center point of the manipulator is specified, and locate the mobile base in the intersection area to guarantee that the end effector can reach all path points.…”

Imitation of Manipulation Skills Using Multiple Geometries

“…In this article, we propose to exploit directional manipulability in the cost function, defined as the length of the manipulability ellipsoid along a particular direction of interest. Tugal et al [52] implement directional manipulability to extend the interaction capabilities of a mobile manipulator on the valve turning task. Kim et al [53] evaluated the maximum directional kinematic capability using optimizationbased methods for redundant manipulators.…”