Visionbased Automatic Control of a 5Fingered Assistive Robotic Manipulator for Activities of Daily Living Assistive Robotic Manipulators (ARMs) play an important role for people with upperlimb disabilities and the elderly by helping them complete Activities of Daily Living (ADLs). However, as the objects to handle in ADLs differ in size, shape and manipulation constraints, many two or three fingered endeffectors of ARMs have difficulty robustly interacting with these objects. In this paper, we propose visionbased control of a 5fingered manipulator (Schunk SVH), automatically changing its approach based on object classification using computer vision combined with deep learning. The control method is tested in a simulated environment and achieves a more robust grasp with the properly shaped fivefingered hand than with a comparable threefingered gripper (Barrett Hand) using the same control sequence. In addition, the final optimal grasp pose (x, y, and theta) is learned through a deep regressor in the penultimate stage of the grasp. This method correctly identifies the optimal grasp pose in 78.35% of cases when considering all three parameters for an object included in the training set, but in a different setting than that of the training set.

A Novel Imagebased Path Planning Algorithm for EyeinHand Visual Servoing of a Redundant Manipulator in a Human Centered Environment This paper presents a novel imagebased pathplanning and execution framework for visionbased control of a robot in a human centered environment. The proposed method involves applying Rapidlyexploring Random Tree (RRT) exploration to perform ImageBased Visual Servoing (IBVS) while satisfying multiple task constraints by exploiting robot redundancy. The methodology incorporates dataset of robotxe2x80x99s workspace images for pathplanning and design a controller based on visual servoing framework. This method is generic enough to include constraints like FieldofView (FoV) limits, joint limits, obstacles, various singularities, occlusions etc. in the planning stage itself using task function approach and thereby avoiding them during the execution. The use of pathplanning eliminates many of the inherent limitations of IBVS with eyeinhand configuration and makes the use of visual servoing practical for dynamic and complex environments. Several experiments have been performed on a UR5 robotic manipulator to demonstrate that it is an effective and robust way to guide a robot in such environments.