Telepresence and telerobotics

The capability for a single operator to simultaneously control complex remote multi degree of freedom robotic arms and associated dextrous end effectors is being developed. An optimal solution within the realm of current technology, can be achieved by recognizing that: (1) machines/computer systems are more effective than humans when the task is routine and specified, and (2) humans process complex data sets and deal with the unpredictable better than machines. These observations lead naturally to a philosophy in which the human's role becomes a higher level function associated with planning, teaching, initiating, monitoring, and intervening when the machine gets into trouble, while the machine performs the codifiable tasks with deliberate efficiency. This concept forms the basis for the integration of man and telerobotics, i.e., robotics with the operator in the control loop. The concept of integration of the human in the loop and maximizing the feed-forward and feed-back data flow is referred to as telepresence

Synchronized computational architecture for generalized bilateral control of robot arms

A master six degree of freedom Force Reflecting Hand Controller (FRHC) is available at a master site where a received image displays, in essentially real time, a remote robotic manipulator which is being controlled in the corresponding six degree freedom by command signals which are transmitted to the remote site in accordance with the movement of the FRHC at the master site. Software is user-initiated at the master site in order to establish the basic system conditions, and then a physical movement of the FRHC in Cartesean space is reflected at the master site by six absolute numbers that are sensed, translated and computed as a difference signal relative to the earlier position. The change in position is then transmitted in that differential signal form over a high speed synchronized bilateral communication channel which simultaneously returns robot-sensed response information to the master site as forces applied to the FRHC so that the FRHC reflects the feel of what is taking place at the remote site. A system wide clock rate is selected at a sufficiently high rate that the operator at the master site experiences the Force Reflecting operation in real time

Performance evaluation of a six-axis generalized force-reflecting teleoperator

Work in real-time distributed computation and control has culminated in a prototype force-reflecting telemanipulation system having a dissimilar master (cable-driven, force-reflecting hand controller) and a slave (PUMA 560 robot with custom controller), an extremely high sampling rate (1000 Hz), and a low loop computation delay (5 msec). In a series of experiments with this system and five trained test operators covering over 100 hours of teleoperation, performance was measured in a series of generic and application-driven tasks with and without force feedback, and with control shared between teleoperation and local sensor referenced control. Measurements defining task performance included 100-Hz recording of six-axis force/torque information from the slave manipulator wrist, task completion time, and visual observation of predefined task errors. The task consisted of high precision peg-in-hole insertion, electrical connectors, velcro attach-de-attach, and a twist-lock multi-pin connector. Each task was repeated three times under several operating conditions: normal bilateral telemanipulation, forward position control without force feedback, and shared control. In shared control, orientation was locally servo controlled to comply with applied torques, while translation was under operator control. All performance measures improved as capability was added along a spectrum of capabilities ranging from pure position control through force-reflecting teleoperation and shared control. Performance was optimal for the bare-handed operator

Learning to Represent Haptic Feedback for Partially-Observable Tasks

The sense of touch, being the earliest sensory system to develop in a human body [1], plays a critical part of our daily interaction with the environment. In order to successfully complete a task, many manipulation interactions require incorporating haptic feedback. However, manually designing a feedback mechanism can be extremely challenging. In this work, we consider manipulation tasks that need to incorporate tactile sensor feedback in order to modify a provided nominal plan. To incorporate partial observation, we present a new framework that models the task as a partially observable Markov decision process (POMDP) and learns an appropriate representation of haptic feedback which can serve as the state for a POMDP model. The model, that is parametrized by deep recurrent neural networks, utilizes variational Bayes methods to optimize the approximate posterior. Finally, we build on deep Q-learning to be able to select the optimal action in each state without access to a simulator. We test our model on a PR2 robot for multiple tasks of turning a knob until it clicks.Comment: IEEE International Conference on Robotics and Automation (ICRA), 201

Robotics 2010

Without a doubt, robotics has made an incredible progress over the last decades. The vision of developing, designing and creating technical systems that help humans to achieve hard and complex tasks, has intelligently led to an incredible variety of solutions. There are barely technical fields that could exhibit more interdisciplinary interconnections like robotics. This fact is generated by highly complex challenges imposed by robotic systems, especially the requirement on intelligent and autonomous operation. This book tries to give an insight into the evolutionary process that takes place in robotics. It provides articles covering a wide range of this exciting area. The progress of technical challenges and concepts may illuminate the relationship between developments that seem to be completely different at first sight. The robotics remains an exciting scientific and engineering field. The community looks optimistically ahead and also looks forward for the future challenges and new development

E-Learning: Case Studies in Web-Controlled Devices and Remote Manipulation

Chances are that distance learning will transparently extend colleges and institutes of education and could plausibly overtake and turn into a preferred choice of higher education, especially for adult and working students. The main idea in e-learning is to build adequate solutions that can assure educational training over the Internet, without requiring a personal presence at the degree offering institution. The advantages are immediate and of unique importance, to enumerate a few: Education costs can be reduced dramatically, both from a student's perspective and the institution's (no need for room and board, for example); The tedious immigration and naturalization issues common with international students are eliminated; The limited campus facilities, faculty members and course schedules an institution can offer are no longer a boundary; Working adults can consider upgrading skills without changing their lifestyles We are presenting through this material a sequence of projects developed at University of Bridgeport and than can serve well in distance learning education ranging from simple "hobby" style training to professional guidance material. The projects have an engineering / laboratory flavor and are being presented in an arbitrary order, topics ranging from vision and sensing to engineering design, scheduling, remote control and operation

Effects of Control Device and Task Complexity on Performance and Task Shedding During a Robotic Arm Task

The use of robotic arms across domains is increasing, but the relationship between control features and performance is not fully understood. The goal of this research was to investigate the difference in task performance when using two different control devices at high and low task complexities when participants can shed tasks to automation. In this experiment, 40 undergraduates (24 females) used two control devices, a Leap Motion controller and an Xbox controller, to teleoperate a robotic arm in a high or low complexity peg placement task. Simultaneously, participants were tasked with scanning images for tanks. During the experiment, participants had the option to task shed the peg task to imperfect automation. Analyses indicated a significant main effect of control device on task completion rate and time to first grasp the peg, with completion rate higher and time lower when using the Leap. However, participants made significantly more errors with the Leap Motion controller than with the Xbox controller. Participants in both conditions task shed similarly with both control devices and task shed at similar times. The 2 x 2 mixed ANOVAs somewhat supported the proposed hypotheses. The results of this study indicate that control device impacts performance on a robotic arm task. The Leap Motion controller supports increased task completion rate and quicker peg grasps in high and low task complexity when compared with the Xbox controller. This supports the extension of Control Order Theory into three-dimensional space and suggests that the Leap Motion controller can be implemented in some domains. However, the criticality and frequency of errors should be carefully considered