Task-level Dexterous Manipulation with Multifingered Hand Under Modeling Uncertainties

This article presents an approach to efficiently control grippers/multifingered hands for dexterous manipulation according to a task, i.e. a predefined trajectory in the object space. The object motion is decomposed using a basis of predefined object motions equivalent to object-level coordinates couplings and leading to the definition of the task-level space. In the proposed approach, the decomposition of the motion in the task space is associated with a robust control design based on Linear Matrix Inequalities (LMIs) and Bilinear Matrix Inequalities (BMI). Eigenvalue placement ensures the robustness of the system to geometric uncertainties and eigenvector placement decouples the system according to task specifications. A practical evaluation of the proposed control strategy is provided with a two-fingers and six-DoFs robotic system manipulating an object in the horizontal plane. Results show a better trajectory tracking and the robustness of the control law according to geometric uncertainties and the manipulation of various objects.

Path Planning for 3-D In-Hand Manipulation of Micro-Objects Using Rotation Decomposition

Robotic manipulation and assembly of micro and nanocomponents in confined spaces is still a challenge. Indeed, the current proposed solutions that are highly inspired by classical industrial robotics are not currently able to combine precision, compactness, dexterity, and high blocking forces. In a previous work, we proposed 2-D in-hand robotic dexterous manipulation methods of arbitrary shaped objects that considered adhesion forces that exist at the micro and nanoscales. Direct extension of the proposed method to 3-D would involve an exponential increase in complexity. In this paper, we propose an approach that allows to plan for 3-D dexterous in-hand manipulation with a moderate increase in complexity. The main idea is to decompose any 3-D motion into a 3-D translation and three rotations about specific axes related to the object. The obtained simulation results show that 3-D in-hand dexterous micro-manipulation of arbitrary objects in presence of adhesion forces can be planned in just few seconds.

Tactile sensory control of the human hand

This chapter details the sensory input from the hand that is mediated by a system of fast-adapting and slowly adapting nerve fibres with a specific anatomical distribution and associations with particular sensory end organs that allow multimodal sensory input and processing. This highly refined system interacts with the motor system to provide continuous feedback that allows the dexterous manipulation of the environment that distinguishes the human hand.

Effects of Aging on Conditional Visuomotor Learning for Grasping and Lifting Eccentrically Weighted Objects

Explicit knowledge of object center of mass or CM location fails to guide anticipatory scaling of digit forces necessary for dexterous manipulation. We previously showed that allowing young adults to choose where to grasp the object entailed an ability to use arbitrary color cues about object CM location to gradually minimize object tilt across several trials. This conditional learning was achieved through accurate anticipatory modulation of digit position using the color cues. However, it remains unknown how aging affects the ability to use explicit color cues about object CM location to modulate digit placement for dexterous manipulation. We instructed healthy older and young adults to learn a manipulation task using arbitrary color cues about object CM location. Subjects were required to exert clockwise, counterclockwise, or no torque on the object according to the color cue and lift the object while minimizing its tilt. Older adults produced larger torque error during conditional learning trials, resulting in a slower rate of learning than young adults. Importantly, older adults showed impaired anticipatory modulation of digit position when information of the CM location was available via explicit color cues. The older adults also did not modulate their digit forces to compensate for this impairment. Interestingly, however, anticipatory modulation of digit position was intact in the same individuals when information of object CM location was implicitly conveyed from trial-to-trial. We discuss our findings in relation to age-dependent changes in processes and neural network essential for learning dexterous manipulation using arbitrary color cue about object property.