Effective methods for human-robot-environment interaction by means of haptic robotics

University of Technology, Sydney. Faculty of Engineering and Information Technology.Industrial robots have been widely used to perform well-defined repetitive tasks in carefully constructed simple environments such as manufacturing factories. The futuristic vision of industrial robots is to operate in complex, unstructured and unknown (or partially known) environments, to assist human workers in undertaking hazardous tasks such as sandblasting in steel bridge maintenance. Autonomous operation of industrial robots in such environments is ideal, but semi-autonomous or manual operation with human interaction is a practical solution because it utilises human intelligence and experience combined with the power and accuracy of an industrial robot. To achieve the human interaction operation, there are several challenges that need to be addressed: environmental awareness, effective robot-environment interaction and human-robot interaction. This thesis aims to develop methodologies that enable natural and efficient Human- Robot-Environment Interaction (HREI) and apply them in a steel bridge maintenance robotic system. Three research issues are addressed: Robot-Environment-Interaction (REI), haptic device and robot interface and intuitive human-robot interaction. To enable efficient robot-environment interaction, a potential field-based Virtual Force Field (VF2) approach has been investigated. The VF2 approach includes an Attractive Force (AF) method and a force control algorithm for robot motion control, and a 3D Virtual Force Field (3D-VF2) method for real-time collision avoidance. Results obtained from simulation, experiments in a laboratory setup and field test have verified and validated these methods. A haptic device-robot interface has been developed for providing intuitive human-robot interaction. Haptic devices are normally small compared to industrial robots. Thus, the workspace of a haptic device is much smaller than the workspace of a big industrial manipulator. A novel workspace mapping method, which includes drifting control, scaling control and edge motion control, has been investigated for mapping a small haptic workspace to the large workspace of manipulator with the aim of providing natural kinesthetic feedback to an operator and smooth control of robot operation. A haptic force control approach has also been studied for transferring the virtual contact force (between the robot and the environment) and the inertia of the manipulator to the operator's hand through a force feedback function. Human factors have significant effect on the performance of haptic-based human-robot interaction. An eXtended Hand Movement (XHM) model for eye-guided hand movement has been investigated in this thesis with the aim of providing natural and comfortable interaction between a human operator and a robot, and improving the operational performance. The model has been studied for increasing the speed of the manipulator while maintaining the control accuracy. This model is applied into a robotic system and it has been verified by various experiments. These theoretical methods and algorithms have been successfully implemented in a steel bridge maintenance robotic system, and tested in both laboratory and a bridge maintenance site located in Sydney

A haptic base human robot interaction approach for robotic grit blasting

This paper proposes a remote operation method for a robot arm in a complex environment by using the Virtual Force (VF) based approach. A virtual robot arm is manipulated by a steering force, at the end-effecter, which is generated according to the movement of a feedback haptic. A three-dimensional force field (3D-F2) is employed in collision detection and avoidance. Repulsive forces from the 3D-F2 are produced and feedback to the haptic device that enables the operator to have a sense of touch on the encountered obstacle and then steer the arm to avoid it. As a result, collision-free poses of the virtual robot arm can then be used to command the real robot. Experiments are conducted in a mock up bridge environment where the real robot arm is steered to target points by the operator. Experiment results have shown successful collision avoidance and emulation of the actual command force and the virtual forces in remote operations

A robotic system for steel bridge maintenance: Research challenges and system design

This paper presents the research on and development of a robotic system for stripping paint and rust from steel bridges, with the ultimate objective of preventing human exposure to hazardous and dangerous debris (containing rust, paint particles, lead and/or asbestos), relieving human workers from labor intensive tasks and reducing costs associated with bridge maintenance. The robot system design, the key research challenges and enabling technologies and system development are discussed in detail. Research results obtained so far and discussions on some key issues are also presented

Workspace mapping and force control for small haptic device based robot teleoperation

When a large robot manipulator is remotely controlled by means of a small haptic device, there are two issues which should be addressed: mapping of robot arm workspace and haptic device workspace, and accurate and safe control of the movement of the robot arm. This paper presents a haptic device workspace spanning control method for haptic-based teleoperation. The spanning control method includes haptic-space scaling control, drift control and edge motion control. A force control algorithm is also presented to control the robot arm's motion in complex 3D environments. Experimental results demonstrate that the mapping method and the force control algorithm can remotely control a robot arm to rapidly reach target positions, minimize the oscillation of the haptic device handle, achieve accurate positioning and provide the operator with efficient touch sensing. © 2009 IEEE

Human-robot-environment interaction interface for robotic grit-blasting of complex steel bridges

This paper presents a human-robot-environment interaction (HREI) interface using haptic feedback for a grit-blasting robot operating in close proximity to a complex steel bridge structure. The productivity requirements dictate the need for efficient algorithms for mapping, exploration, and collision-free motion planning. While a large portion of the grit-blasting operation can be automated, a tele-operation is essential to deal with some difficult to access sections such as edges, complex corners, and surfaces which can only be approached through hole. A 3-dimensional virtual force field (3D-VF 2) method is developed for capturing the relationship between the robot and its environment. A novel haptic force generation method and a workspace mapping algorithm allow intuitive interaction between the operator and the robot through haptic feedback. The strategies presented are verified in extensive simulations and experiments conducted on a steel bridge with a prototype grit-blasting robot. © 2012 Elsevier B.V

Effect of view distance and movement scale on haptic-based teleoperation of industrial robots in complex environments

This paper presents the study on the effect of view distance and movement scale on performance of haptic based teleoperation of a sandblasting robot in complex steel bridge maintenance environments. The operational performance, measured by the Index of Performance (IP), is defined based on the speed and the control accuracy of the manipulator. View distance (i.e. the distance between a display space and an object movement space) and movement scale between hand movement and manipulator movement, which are normally selected empirically, have significant effect the performance. In this paper, an experimental approach is used for determining view distance and movement scale. The sandblasting robotic system is used as an example industrial application in the experiments. Results of the experiments show a range of the view distance and the movement scale that can improve the performance of haptic-based teleoperation of industrial robots in complex environments