An assisted telemanipulation approach: combining autonomous grasp planning with haptic cues This paper presents an assisted telemanipulation approach with integrated grasp planning. It also studies how the human teleoperation performance benefits from the incorporated visual and haptic cues while manipulating objects in cluttered environments. The developed system combines the widely used masterslave teleoperation with our previous modelfree and learningfree grasping algorithm by means of a dynamic grasp reranking strategy and a semiautonomous reachtograsptrajectory guidance. The proposed reranking metric helps in dynamically updating the stable grasps based on the current state of the slave device. The trajectory guidance system assists in maintaining smooth trajectory by controlling the haptic forces. A virtual pose controller has been integrated with the guidance scheme to automatically correct the endeffector orientation while reaching towards the grasp. Various experiments are conducted evaluating the proposed method using a six degrees of freedom (dof) haptic master and a seven dof slave robot. Results obtained with these tests along with the results gathered from the performed humanfactor trials demonstrate the efficiency of our method in terms of objective metrics of task completion, and also subjective metrics of user experience.

An Intuitive, Affordances Oriented Telemanipulation Framework for a Dual Robot Arm Hand System: On the Execution of Bimanual Tasks The concept of teleoperation has been studied since the advent of robotics and has found use in a wide range of applications, including exploration of remote or dangerous environments (e.g., space missions, disaster management), telepresence based time optimisation (e.g., remote surgery) and robot learning. While a significant amount of research has been invested into the field, intricate manipulation tasks still remain challenging from the user perspective due to control complexity. In this paper, we propose an intuitive, affordances oriented telemanipulation framework for a dual robot arm hand system. An object recognition module is utilised to extract scene information and provide grasping and manipulation assistance to the user, simplifying the control of adaptive, multifingered hands through a commercial Virtual Reality (VR) interface. The systemxe2x80x99s performance was experimentally validated in a remote operation setting, where the user successfully performed a set of bimanual manipulation tasks.