Factors that influence reliable object manipulation

This paper presents various factors that influencerobotic object manipulation. Some of these factors are inherentto the object and mostly unavoidable, while others arecontrollable by the grasping and slippage control systemdesigner. Some factors, such as object texture are obviouslyinherent to the object and unavoidable for the purpose of objectmanipulation. However, other factors, such as the choice ofmechanism control resolution depend mostly on the designer. Itis anticipated that this information will be helpful to designers ofrobotic object grasping and slippage control systems, and willcontribute to better design decisions

A depth sensor to control pick-and-place robots for fruit packaging

This paper presents a powerful and inexpensive automated object detection and localization method for pick-and-place robots using a low cost, commercial 3D depth sensor.The robot control application developed for this project extracts relevant information such as the XYZ co-ordinates of an object’s location from a 3D depth map, generated by the depth sensor interface software. This information is then used by the robot control application to control a pick-and-place robot for handling object/fruit. Experiments have proven that object’s projected area and orientation can be extracted from the depth map provided by the 3D depth sensor. This type of depth sensor can be used in robotics research projects for short range environment mapping and navigation and for object detection and locating

Modelling of a grasping and manipulation controller

This paper presents the development of a robot grasping and manipulation control system, including the modelling approach for the control functions, and the criteria used for functional module design in order to achieve the required functionality and allow its integration into the overall control model. This work is an example of a practical implementation of a robotic grasping and manipulation controller and may be relevant to researchers looking for an example of a practical controller design “from scratch”

A robotic palletiser control strategy redesign

This paper presents the design changes to the control strategy of a robotic palletising machine that was developed earlier. The changes were required in order to simplify maintenance, and to enhance reliability and robustness. The updated control system uses a distributed control configuration to minimise control complexity and maximise functionality. The main benefit of the lower complexity distributed control is a more robust and “intelligent” control that provides better feedback to operators and maintenance personnel. This in turn translates into less machine downtime,and not surprisingly happier people.There are several lessons to be learned from this control system redesign, some of which are technical and some relate to the challenges of getting the appropriate stakeholders to "buy" into the project

An advanced control strategy for robotic palletiser in materials handling for higher productivity

This paper presents the strategic control system of a robotic palletising system for a production company to achieve higher level automation and higher productivity as well as user-friendly operation. The control configuration consists of a graphical application running on a human-machine interface (HMI) touch screens interfaced to a programmable logic controller (PLC), and a servo system that executes palletiser reconfiguration and makes high-speed robotic palletizing possible. Significant downtime reduction during batch changes is achieved due to simplification of operator tasks, which makes the configuration and control method ideally suitable for production environments with frequent batch changes

Principles of sensor technologies for object recognition and grasping

Tactile sensing has been recognised as an important sensing modality in robotic object recognition and manipulation tasks. There are two main robotic tactile sensors: those flexible and lower resolutions intended for robot skin applications, and those intended for robot hand and finger applications that are typically higher resolution. The tactile sensors intended for use as robot body skin are typically lower resolution sensors and in many cases can be simple sensors that detect when the skin has been touched. Depending on the intended sophistication of the application, these can be simple binary on-off sensors or more complex sensors that detect normal and tangential forces acting on the skin. To fulfil all robotic tactile sensory needs with a single type of sensor is close to impossible. Therefore most transduction principles have been used in the tactile sensor development including capacitive, resistive/conductive, piezoelectric, pyroelectric, piezoresistive, optic, ultrasonic, magnetic, magneto-electric, mechanical (on/off) and quantum tunnelling. This paper briefly presents the working principles of sensors in these categories

Modeling of an object manipulation motion planner and grasping rules

This paper presents the development of a Motion Planning Module for object manipulation, which is a part of previously developed robotic grasping and manipulation controller. The Motion Planning Module consists of a sensing processor, decision making module, instinctive controller, motion planner and a planned motion controller. Details related to the design and modelling of the motion planning module have been offered. Results of experiments on human grasping rule, suitable for the grasping and manipulation controller, have been discussed. The output of this research may be useful to those developing motion planning strategies for their grasping and manipulation controllers

A method to control grip force and slippage for robotic object grasping and manipulation

A grip force and slippage control for robotic object manipulation, based on mechanical friction is presented. This approach allows a load to be held reliably in the robot gripper without application of excessive forces or allowing uncontrolled slippage. It is a simple, robust and low cost solution, and could be used for applications where low cost integrated grip force and slippage control are needed. This solution could be customized to provide reliable grip force and slippage control for light, medium or heavy load holding applications for a variety of different objects

Analysis of sensor and gripper jaw response times

This paper presents the importance of designing a robotic grasping mechanism from the mechanical resolution and sensing resolution perspective. A low grasping system mechanical resolution defeats the purpose of high sensing resolution. A low sensing resolution capability defeats the purpose of a high mechanical control resolution. In either case the result is inadequate grasping control for precision grasping. An adequate balance is required between sensing and mechanical resolutions to maximize the potential of both. Grasping mechanism’s grasp range and sensing range are important as well, because these affect slippage control, precision grasping, and safe object manipulation

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 graspand 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