A framework of teleoperated and stereo vision guided mobile manipulation for industrial automation

Smart and flexible manufacturing requests the adoption of industrial mobile manipulators in factory. The goal of autonomous mobile manipulation is the execution of complex manipulation tasks in unstructured and dynamic environments. It is significant that a mobile manipulator is able to detect and grasp the object in a fast and accurate manner. In this research, we developed a stereo vision system providing qualified point cloud data of the object. A modified and improved iterative closest point algorithm is applied to recognize the targeted object greatly avoiding the local minimum in template matching. Moreover, a stereo vision guided teleoperation control algorithm using virtual fixtures technology is adopted to enhance robot teaching ability. Combining these two functions, the mobile manipulator is able to learn semi-autonomously and work autonomously. The key components and the system performance are then tested and proved in both simulation and experiments

Model Based Teleoperation to Eliminate Feedback Delay NSF Grant BCS89-01352 Second Report

We are conducting research in the area of teleoperation with feedback delay. Delay occurs with earth-based teleoperation in space and with surface-based teleoperation with untethered submersibles when acoustic communication links are involved. The delay in obtaining position and force feedback from remote slave arms makes teleoperation extremely difficult leading to very low productivity. We have combined computer graphics with manipulator programming to provide a solution to the problem. A teleoperator master arm is interfaced to a graphics based simulator of the remote environment. The system is then coupled with a robot manipulator at the remote, delayed site. The operator\u27s actions are monitored to provide both kinesthetic and visual feedback and to generate symbolic motion commands to the remote slave. The slave robot then executes these symbolic commands delayed in time. While much of a task proceeds error free, when an error does occur, the slave system transmits data back to the master environment which is then reset to the error state from which the operator continues the task

A robot learning method with physiological interface for teleoperation systems

The human operator largely relies on the perception of remote environmental conditions to make timely and correct decisions in a prescribed task when the robot is teleoperated in a remote place. However, due to the unknown and dynamic working environments, the manipulator's performance and efficiency of the human-robot interaction in the tasks may degrade significantly. In this study, a novel method of human-centric interaction, through a physiological interface was presented to capture the information details of the remote operation environments. Simultaneously, in order to relieve workload of the human operator and to improve efficiency of the teleoperation system, an updated regression method was proposed to build up a nonlinear model of demonstration for the prescribed task. Considering that the demonstration data were of various lengths, dynamic time warping algorithm was employed first to synchronize the data over time before proceeding with other steps. The novelty of this method lies in the fact that both the task-specific information and the muscle parameters from the human operator have been taken into account in a single task; therefore, a more natural and safer interaction between the human and the robot could be achieved. The feasibility of the proposed method was demonstrated by experimental results

Teleprogramming: Overcoming Communication Delays in Remote Manipulation (Dissertation Proposal)

Modern industrial processes (nuclear, chemical industry), public service needs (firefighting, rescuing), and research interests (undersea, outer space exploration) have established a clear need to perform work remotely. Whereas a purely autonomous manipulative capability would solve the problem, its realization is beyond the state of the art in robotics [Stark et al.,1988]. Some of the problems plaguing the development of autonomous systems are: a) anticipation, detection, and correction of the multitude of possible error conditions arising during task execution, b) development of general strategy planning techniques transcending any particular limited task domain, c) providing the robot system with real-time adaptive behavior to accommodate changes in the remote environment, d) allowing for on-line learning and performance improvement through experience , etc. The classical approach to tackle some of these problems has been to introduce problem solvers and expert systems as part of the remote robot workcell control system. However, such systems tend to be limited in scope (to remain intellectually and implementationally manageable), too slow to be useful in real-time robot task execution, and generally fail to adequately represent and model the complexities of the real world environment. These problems become particularly severe when only partial information about the remote environment is available

An intelligent, free-flying robot

The ground based demonstration of the extensive extravehicular activity (EVA) Retriever, a voice-supervised, intelligent, free flying robot, is designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The major objective of the EVA Retriever Project is to design, develop, and evaluate an integrated robotic hardware and on-board software system which autonomously: (1) performs system activation and check-out; (2) searches for and acquires the target; (3) plans and executes a rendezvous while continuously tracking the target; (4) avoids stationary and moving obstacles; (5) reaches for and grapples the target; (6) returns to transfer the object; and (7) returns to base

Redesigning the human-robot interface : intuitive teleoperation of anthropomorphic robots

textA novel interface for robotic teleoperation was developed to enable accurate and highly efficient teleoperation of the Industrial Reconfigurable Anthropomorphic Dual-arm (IRAD) system and other robotic systems. In order to achieve a revolutionary increase in operator productivity, the bilateral/master-slave approach must give way to shared autonomy and unilateral control; autonomy must be employed where possible, and appropriate sensory feedback only where autonomy is impossible; and today’s low-information/high feedback model must be replaced by one that emphasizes feedforward precision and minimal corrective feedback. This is emphasized for task spaces outside of the traditional anthropomorphic scale such as mobile manipulation (i.e. large task spaces) and high precision tasks (i.e. very small task spaces). The system is demonstrated using an anthropomorphically dimensioned industrial manipulator working in task spaces from one meter to less than one millimeter, in both simulation and hardware. This thesis discusses the design requirements and philosophy of this interface, provides a summary of prototype teleoperation hardware, simulation environment, test-bed hardware, and experimental results.Mechanical Engineerin

Model Based Teleoperation to Eliminate Feedback Delay NSF Grant BCS89-01352 First Report

We are conducting research in the area of teleoperation with feedback delay. Delay occurs with earth-based teleoperation in space and with surface-based teleoperation with untethered submersibles when acoustic communication links are involved. the delay in obtaining position and force feedback from remote slave arms makes teleoperation extremely difficult. We are proposing a novel combination of graphics and manipulator programming to solve the problem by interfacing a teleoperator master arm to a graphics based simulator of the remote environment coupled with a robot manipulator at the remote, delayed site. the operator\u27s actions will be monitored to provide both kinesthetic and visual feedback and to generate symbolic motion commands to the remote slave. the slave robot will then execute these symbolic commands delayed in time. While much of a task will proceed error free, when an error does occur the slave system will transmit data back to the master and the master environment will be reset to the error state

Exploring Robot Teleoperation in Virtual Reality

This thesis presents research on VR-based robot teleoperation with a focus on remote environment visualisation in virtual reality, the effects of remote environment reconstruction scale in virtual reality on the human-operator's ability to control the robot and human-operator's visual attention patterns when teleoperating a robot from virtual reality. A VR-based robot teleoperation framework was developed, it is compatible with various robotic systems and cameras, allowing for teleoperation and supervised control with any ROS-compatible robot and visualisation of the environment through any ROS-compatible RGB and RGBD cameras. The framework includes mapping, segmentation, tactile exploration, and non-physically demanding VR interface navigation and controls through any Unity-compatible VR headset and controllers or haptic devices. Point clouds are a common way to visualise remote environments in 3D, but they often have distortions and occlusions, making it difficult to accurately represent objects' textures. This can lead to poor decision-making during teleoperation if objects are inaccurately represented in the VR reconstruction. A study using an end-effector-mounted RGBD camera with OctoMap mapping of the remote environment was conducted to explore the remote environment with fewer point cloud distortions and occlusions while using a relatively small bandwidth. Additionally, a tactile exploration study proposed a novel method for visually presenting information about objects' materials in the VR interface, to improve the operator's decision-making and address the challenges of point cloud visualisation. Two studies have been conducted to understand the effect of virtual world dynamic scaling on teleoperation flow. The first study investigated the use of rate mode control with constant and variable mapping of the operator's joystick position to the speed (rate) of the robot's end-effector, depending on the virtual world scale. The results showed that variable mapping allowed participants to teleoperate the robot more effectively but at the cost of increased perceived workload. The second study compared how operators used a virtual world scale in supervised control, comparing the virtual world scale of participants at the beginning and end of a 3-day experiment. The results showed that as operators got better at the task they as a group used a different virtual world scale, and participants' prior video gaming experience also affected the virtual world scale chosen by operators. Similarly, the human-operator's visual attention study has investigated how their visual attention changes as they become better at teleoperating a robot using the framework. The results revealed the most important objects in the VR reconstructed remote environment as indicated by operators' visual attention patterns as well as their visual priorities shifts as they got better at teleoperating the robot. The study also demonstrated that operators’ prior video gaming experience affects their ability to teleoperate the robot and their visual attention behaviours