Flexible representations of dynamics are used in object manipulation.

To manipulate an object skillfully, the brain must learn its dynamics, specifying the mapping between applied force and motion. A fundamental issue in sensorimotor control is whether such dynamics are represented in an extrinsic frame of reference tied to the object or an intrinsic frame of reference linked to the arm. Although previous studies have suggested that objects are represented in arm-centered coordinates [1-6], all of these studies have used objects with unusual and complex dynamics. Thus, it is not known how objects with natural dynamics are represented. Here we show that objects with simple (or familiar) dynamics and those with complex (or unfamiliar) dynamics are represented in object- and arm-centered coordinates, respectively. We also show that objects with simple dynamics are represented with an intermediate coordinate frame when vision of the object is removed. These results indicate that object dynamics can be flexibly represented in different coordinate frames by the brain. We suggest that with experience, the representation of the dynamics of a manipulated object may shift from a coordinate frame tied to the arm toward one that is linked to the object. The additional complexity required to represent dynamics in object-centered coordinates would be economical for familiar objects because such a representation allows object use regardless of the orientation of the object in hand.

Neural networks engaged in tactile object manipulation: patterns of expression among healthy individuals

Somatosensory object discrimination has been shown to involve widespread cortical and subcortical structures in both cerebral hemispheres. In this study we aimed to identify the networks involved in tactile object manipulation by principal component analysis (PCA) of individual subjects. We expected to find more than one network.

Robotic object grasping in context of human grasping and manipulation

This paper presents experimental and deductive findings that shed new light on grasp force estimation, which improves robot’s chances to grasp and manipulate the object close to optimum conditions on the first attempt, which in turn improves robot’s object manipulation dexterity.
This paper proposes that object slippage detection in the human hand is not detected based purely on microvibrations sensed by the human skin during incipient slippage but also on load sensing at each finger and movement of fingers relative to each other while holding an object.

Object grasping and safe manipulation using friction-based sensing.

This project provides a solution for slippage prevention in industrial robotic grippers for the purpose of safe object manipulation. Slippage sensing is performed using novel friction-based sensors, with customisable slippage sensitivity and complemented by an effective slippage prediction strategy. The outcome is a reliable and affordable slippage prevention technology.

Improving robot vision models for object detection through interaction

We propose a method for learning specific object representations that can be applied (and reused) in visual detection and identification tasks. A machine learning technique called Cartesian Genetic Programming (CGP) is used to create these models based on a series of images. Our research investigates how manipulation actions might allow for the development of better visual models and therefore better robot vision. This paper describes how visual object representations can be learned and improved by performing object manipulation actions, such as, poke, push and pick-up with a humanoid robot. The improvement can be measured and allows for the robot to select and perform the `right' action, i.e. the action with the best possible improvement of the detector.

Heavy tools manipulation by low powered direct-drive five-bar parallel robot

This paper presents a simple and available system for manipulation of heavy tools by low powered manipulator for industrial applications. In the heavy manufacturing industries, sometimes, heavy tools are employed for different types of work. But the application of robots with heavy tools is not possible due to the limited torque limits of actuators. Suspended tool systems (STS) have been proposed to manipulate heavy tools by low powered robot-arm for this purpose. A low powered five-bar direct-drive parallel manipulator is designed and constructed to manipulate heavy tools suspended from a spring balancer. The validity, usefulness, and effectiveness of the suspended tool system are shown by experimental results.

A haptic platform to enable fingertip grasping and manipulation

Haptic technologies allow human users to haptically interact with virtual environments. Haptics has been employed in many application domains including operator training, virtual exploration and teleoperation. Currently, most commercially available haptic devices focus on a single point of haptic interaction. While single-point haptics have been successfully employed in many applications, they remain limited to particular types of haptic interaction. Multi-point haptic devices are a logical progression and facilitate a far wider range of interactions including object grasping, multi-finger object manipulation and size discrimination. The ability to effectively achieve such interactions offers significant benefits for many applications including virtual training, telesurgery and telemanipulation. In such applications, the ability to use multi-point haptic interactions can provide far more effective user interaction as well improved perception of the virtual environment.

Robotic grasping and manipulation controller framework: architecture redevelopment

This paper details the further improvements obtained by redesigning a previously offered Manipulation Controller Framework to provide support to an innovative, friction-based object slippage detection strategy employed by the robotic object manipulator. This upgraded Manipulation Controller Framework includes improved slippage detection functionality and a streamlined architecture designed to improve controller robustness, reliability and speed. Improvements include enhancements to object slippage detection strategy, the removal of the decision making module and integration of its functionality into the Motion Planner, and the stream-lining of the Motion Planner to improve its effectiveness. It is anticipated that this work will be useful to researchers developing integrated robot controller architectures and slippage control.

Grip and load force coordination in cyclical isometric manipulation task is not affected by the feedback type

Background: The relationship between normal and tangential force components (grip force - GF and load force - LF, respectively) acting on the digits-object interface during object manipulation reveals neural mechanisms involved in movement control. Here, we examined whether the feedback type provided to the participants during exertion of LF would influence GF-LF coordination and task performance. Methods. Sixteen young (24.7 ±3.8 years-old) volunteers isometrically exerted continuously sinusoidal FZ (vertical component of LF) by pulling a fixed instrumented handle up and relaxing under two feedback conditions: targeting and tracking. In targeting condition, FZ exertion range was determined by horizontal lines representing the upper (10 N) and lower (1 N) targets, with frequency (0.77 or 1.53 Hz) dictated by a metronome. In tracking condition, a sinusoidal template set at similar frequencies and range was presented and should be superposed by the participants' exerted FZ. Task performance was assessed by absolute errors at peaks (AEPeak) and valleys (AEValley) and GF-LF coordination by GF-LF ratios, maximum cross-correlation coefficients (r max), and time lags. Results: The results revealed no effect of feedback and no feedback by frequency interaction on any variable. AE Peak and GF-LF ratio were higher and rmax lower at 1.53 Hz than at 0.77 Hz. Conclusion: These findings indicate that the type of feedback does not influence task performance and GF-LF coordination. Therefore, we recommend the use of tracking tasks when assessing GF-LF coordination during isometric LF exertion in externally fixed instrumented handles because they are easier to understand and provide additional indices (e.g., RMSE) of voluntary force control. © 2013 Pedão et al.; licensee BioMed Central Ltd.