Fundamentals of Robot Technology

Todd, D. J.

doi:10.1007/978-94-011-6768-0

Cited by 33 publications

(8 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These techniques enable robots to learn motion trajectories (Delson and West 1996) or manipulation tasks (e.g., Yang, Xu, and Chen 1993). Using such "lead-through" teaching approaches (Todd 1986) requires that the demonstration be performed by a skilled teacher, as the performance of the teacher in demonstrating the task has a great influence on the learned capabilities. Another difficulty that may arise in teleoperation is that the training may be performed through instruments that are different than what the human operator would use in accomplishing the task.…”

Section: Related Workmentioning

confidence: 99%

A Training Simulation System With Realistic Autonomous Ship Control

Nicolescu

Leigh

Olenderski

et al. 2007

Computational Intelligence

View full text Add to dashboard Cite

In this article we present a computational approach to developing effective training systems for virtual simulation environments. In particular, we focus on a Naval simulation system, used for training of conning officers. The currently existing training solutions require multiple expert personnel to control each vessel in a training scenario, or are cumbersome to use by a single instructor. The inability of current technology to provide an automated mechanism for competitive realistic boat behaviors thus compromises the goal of flexible, anytime, anywhere training. In this article we propose an approach that reduces the time and effort required for training of conning officers, by integrating novel approaches to autonomous control within a simulation environment. Our solution is to develop intelligent, autonomous controllers that drive the behavior of each boat. To increase the system's efficiency we provide a mechanism for creating such controllers, from the demonstration of a navigation expert, using a simple programming interface. In addition, our approach deals with two significant and related challenges: the realism of behavior exhibited by the automated boats and their real-time response to changes in the environment. In this article, we describe the control architecture we developed that enables the real-time response of boats and the repertoire of realistic behaviors we designed for this application. We also present our approach for facilitating the automatic authoring of training scenarios and we demonstrate the capabilities of our system with experimental results.

show abstract

Section: Related Workmentioning

confidence: 99%

A Training Simulation System With Realistic Autonomous Ship Control

Nicolescu

Leigh

Olenderski

et al. 2007

Computational Intelligence

View full text Add to dashboard Cite

show abstract

“…Two of the most common industrial applications are spray painting and spot welding. Both of these use natural programming methods such as "lead-through teaching" [Todd 1986] (a primitive form of human demonstration) and point-teaching, respectively, that are easily mastered by semiskilled workers because of their intuitiveness. Lead-through teaching, in particular, allows anyone who can perform a "valid" task to program the robot to perform the same task simply by demonstrating it.…”

Section: Gesture-based Programming For Roboticsmentioning

confidence: 99%

Gesture-based programming for robotics: human-augmented software adaptation

Voyles¹,

Morrow²,

Khosla³

1999

IEEE Intell. Syst.

View full text Add to dashboard Cite

Gesture-Based Programming is a paradigm for programming robots by human demonstration in which the human demonstrator directs the self-adaptation of executable software. The goal is to provide a more natural environment for the user as programmer and to generate more complete and successful programs by focusing on task experts rather than programming experts. We call the paradigm "gesture-based" because we try to enable the system to capture, in real-time, the intention behind the demonstrator's fleeting, context-dependent hand motions, contact conditions, finger poses, and even cryptic utterances in order to reconfigure itself. The system is self-adaptive in the sense that knowledge of previously acquired skills (sensorimotor expertise) is retained by the system and this knowledge facilitates the interpretation of the gestures during training and then provides feedback control during run-time. INTRODUCTIONThe text-based programming paradigm relies exclusively on the expertise of the human programmer and his or her ability to learn from and remember past lessons on system development. Beyond on-line help files, the applications themselves and the programming environments that facilitate their creation acquire no knowledge of themselves and carry-over no useful knowledge from project to project or even within the development of a single project. The burden of retaining the expertise that results from the creation of new applications or new configurations of existing applications falls entirely on the human programmer. The idea behind self-adaptive software is to empower the system itself to participate in its own development. If a software environment can retain a knowledge base of its own capabilities and usefulness, it can assist the human developer during reapplication or reconfiguration and potentially perform autonomous adaptation. The allowable degree of "self-determination" will certainly vary across applications and operating environments. For example, the user interface to a consumer application program may have wide latitude for self-adaptation on an ongoing basis. A manufacturing system, on the other hand, would likely have rigid constraints on the degree of allowable self-adaptation and even on the periods during which self-adaptation is enabled. GESTURE-BASED PROGRAMMING FOR ROBOTICSThe focus of this paper is not the grand goal of self-adaptive software, but a smaller step toward it we call human-augmented adaptation. We further limit our efforts to the task of robot programming. In particular, we are interested in the programming paradigm itself and in finding alternative approaches to programming that are more intuitive for human users. Our basic model is human-to-human training, which is very intuitive to users. In this model, the trainee is active in the process, so, when applied to the programming of robotic systems, it naturally leads to systems that are more participative in their own development. In this sense, human-augmented adaptation is an important step toward, and a useful compl...

show abstract

“…These errors can be described by an accuracy and a precision or repeatability term. These are similar to the target shooting accuracy and precision errors [Todd, D.J., 1986] but now they have to be defined for a three dimensional space six degrees of freedom case (position and orientation). To-Point control operation might require the knowledge of the manipulator resolution, which is the minimum displacement in three dimensional space (position and orientation) by which can a manipulator move its end-effector.…”

Section: Robot Performancementioning

confidence: 99%

Robot characterization testing

Dagalakis¹

1991

View full text Add to dashboard Cite

show abstract

Fundamentals of Robot Technology

Cited by 33 publications

References 8 publications

A Training Simulation System With Realistic Autonomous Ship Control

A Training Simulation System With Realistic Autonomous Ship Control

Gesture-based programming for robotics: human-augmented software adaptation

Robot characterization testing

Contact Info

Product

Resources

About