Current robot programming approaches lack the intuitiveness required for quick and simple applications. As new robotic applications are being identified, there is a greater need to be able to programme robots safely a...
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Current robot programming approaches lack the intuitiveness required for quick and simple applications. As new robotic applications are being identified, there is a greater need to be able to programme robots safely and quickly. This paper discusses the use of an augmented reality (AR) environment for facilitating intuitive robot programming, and presents a novel methodology for planning collision-free paths for an n-d.o.f. (degree-of-freedom) manipulator in a 3D AR environment. The methodology is interactive because the human is involved in defining the free space or collision-free volume (CFV), and selecting the start and goal configurations. The methodology uses a heuristic beam search algorithm to generate the paths. A number of possible scenarios are discussed. (C) 2008 Elsevier Ltd. All rights reserved.
Programmable robotics is recently used in early childhood education (ECE) to introduce programming and computational thinking (CT) skills. However, there is a further need for research to contrast the efficacy of chil...
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Programmable robotics is recently used in early childhood education (ECE) to introduce programming and computational thinking (CT) skills. However, there is a further need for research to contrast the efficacy of children's participation in robot programming and traditionally beneficial ECE activities. The present study thus investigated the effects of a robot programming intervention versus a block play program on kindergarteners' CT, sequencing ability, and self-regulation. The experiment (robot programming) versus comparison (block play) condition was randomly assigned to four kindergarten classes, which included 101 kindergarteners (M = 64.78 months, SD = 7.64). Statistical analyses revealed that the robot programming group (N = 54) had experienced greater gains over time in sequencing ability relative to those in the block play group (N = 47;F = 5.09, p < 0.05). Children in the robot programming group with lower level of self-regulation at baseline showed larger improvements in sequencing ability over time relative to the block play group (F = 2.37, p = 0.01). Also, children in the robot programming group with older age showed larger improvements in CT over time relative to the block play group (F = 2.40, p < 0.01). The study demonstrates the positive benefits of robot programming to early childhood development in terms of CT and sequencing ability, compared to a traditional curriculum activity in ECE-block play.
Programmable and non-programmable educational robots are, in most cases, associated with sedentary behavior in children. Children interact with educational robots mostly in indoor environments. Whole-body interaction ...
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ISBN:
(纸本)9783319653402;9783319653396
Programmable and non-programmable educational robots are, in most cases, associated with sedentary behavior in children. Children interact with educational robots mostly in indoor environments. Whole-body interaction and natural environments seem to potentiate children's physical and mental health. In order to potentiate children's physical and mental health we have developed a new set of robotic devices -Biosymtic robotic devices. We describe the main computational models of Biosymtic robotic devices: a computational model demonstrating how to increase children's physical activity levels and contact with natural environments through automatic feedback control mechanisms;a theoretical cognitive model on how to program robotic devices through whole-body interaction in natural environments.
This study proposes an alternative approach for the generation of robot trajectories which is extended to include three dimensional motion. The presence of human inconsistency is used to improve robot performance by g...
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ISBN:
(纸本)0780319338
This study proposes an alternative approach for the generation of robot trajectories which is extended to include three dimensional motion. The presence of human inconsistency is used to improve robot performance by generating robot trajectories that are shorter than the demonstrated ones and with the addition of a buffer between the robot and the obstacles.
programming by Human Demonstration (PHD) is an intuitive method of robot programming, in which the programmer demonstrates how a task is performed using a human/robot interface device that measures human position and ...
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ISBN:
(纸本)0780308239
programming by Human Demonstration (PHD) is an intuitive method of robot programming, in which the programmer demonstrates how a task is performed using a human/robot interface device that measures human position and applied force, and the data gathered is used to generate the robot program. Applying PHD to simple position control tasks is straightforward;the robot plays back the demonstrated position trajectory. However, for assembly tasks variation in part location requires that the robot adapt to the environment. A PHD method `playback of compliance trajectory' is presented which utilizes compliance control to duplicate the human position and force trajectories when the parts being assembled are in the same location as during the demonstration, and will successfully adapt to certain variations in part location. To identify an appropriate compliance that will guarantee successful assembly, a second approach is presented that is based on multiple demonstrations. The demonstrator performs the task with eyes closed and is restricted to using only position and force information, and variations in part location are introduced between the demonstrations. A criterion for selecting a compliance matrix is identified so that the robot errors in position and the maximum contact force will be less than those of the human, and that the robot will be able to achieve this level of performance as long as variation in workpiece location is not larger than during the demonstrations. The analysis is restricted to tasks which are demonstrated with a consistent sequence of subtasks, where each subtask consists of straight line translational motion. In the case of constrained translational motion there are two possible configurations, a single direction of constraint and two directions of constraint, which cannot be uniquely determined from the demonstration data, and the compliance controller is selected to be successful in either constraint configuration.
Increasingly, personalised robots - robots especially designed and programmed for an individual's needs and preferences - are being used to support humans in their daily lives, most notably in the area of service ...
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ISBN:
(纸本)9781424409129
Increasingly, personalised robots - robots especially designed and programmed for an individual's needs and preferences - are being used to support humans in their daily lives, most notably in the area of service robotics. Arguably, the closer the robot is programmed to the individual's needs, the more useful it is, and we believe that giving people the opportunity to program their own robots, rather than programmingrobots for them, will push robotics research one step further in the personalised robotics field. However, traditional robot programming techniques require specialised technical skills from different disciplines and it is not reasonable to expect end-users to have these skills. In this paper, we therefore present a new method of obtaining robot control code - programming by demonstration through system identification - which algorithmically and automatically transfers human behaviours into robot control code, using transparent, analysable mathematical functions. Besides providing a simple means of generating perception-action mappings, they have the additional advantage that can also be used to form hypotheses and theoretical analysis of robot behaviour. We demonstrate the viability of this approach by teaching a Scitos G5 mobile robot to achieve wall following and corridor passing behaviours.
programming by Human Demonstration is an intuitive method of robot programming, in which the programmer demonstrates how a task is performed using a human/robot teaching device that measures human motion, and the data...
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ISBN:
(纸本)0818653302
programming by Human Demonstration is an intuitive method of robot programming, in which the programmer demonstrates how a task is performed using a human/robot teaching device that measures human motion, and the data gathered is used to generate the robot program. A direct duplication of the demonstrated trajectory would result in unnecessary robot motion due to human `wiggles' and unintended motion. To identify a more satisfactory robot trajectory, a method is presented that uses multiple demonstrations of the same task. Variation in human trajectories between trials is attributed to human inconsistency and is used to define an obstacle free region, by applying the Jordan curve theorem. The shortest path within the obstacle free region is determined, resulting in a shorter robot path than any of the demonstrations. Thus the presence of human inconsistency is used to improve robot performance. The analysis is restricted to planar translational motion.
This paper presents a framework for robot programming by human demonstration. The framework builds a high level robot controller using information extracted from the demonstration. The high level robot controller is b...
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ISBN:
(纸本)078034300X
This paper presents a framework for robot programming by human demonstration. The framework builds a high level robot controller using information extracted from the demonstration. The high level robot controller is broken down into three component parts, each fulfilling a different function during execution. This paper focuses on the construction of an Event Path Planner which determines the optimal event path of a task. The approach varies the optimal path according to what characteristics of the demonstrations are stressed, thus giving the robot a selected disposition. The approach was implemented on a simple navigational task. The Event Path Planner selected appropriate paths and could change its selection according to what characteristics were desired in the selected path.
Human-robot interaction issues, especially for industrial robots, have largely been confined to finding better ways to reconfigure or program the robots. In this paper, air Augmented Reality based robot programming (R...
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ISBN:
(纸本)9781424448647
Human-robot interaction issues, especially for industrial robots, have largely been confined to finding better ways to reconfigure or program the robots. In this paper, air Augmented Reality based robot programming (RPAR-II) system is proposed. A virtual robot, which is a replicate of a real robot, is used in a real environment to perform and simulate the robot trajectory planning process. The RPAR-II system assists the users during the robot programming process from task planning to execution. Stereo vision-based methodologies for virtual objects registration as well as interactive device position tracking are employed in this system. Practical issues concerning the system implementation are discussed.
Today's industrial robots require that human operators teach motions in advance. However, conventional methods for robot programming need deep knowledge and skills about robots or great effort for inputting inform...
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ISBN:
(纸本)9781509067817
Today's industrial robots require that human operators teach motions in advance. However, conventional methods for robot programming need deep knowledge and skills about robots or great effort for inputting information of working environment into computers. Therefore, a robot programming method in which everyone can easily teach robots "good" motions is demanded. For this purpose, our group proposed a robot programming method that uses manual volume sweeping by operators and automatic motion planning together to generate motion plans with short cycle times. Because a swept volume is the space through which the robot has passed without collision, it is movable space of the robot that can be used in motion planning. In this paper, we proposed using augmented reality in this programming method. We constructed a system in which operators can perceive obtained swept volumes and generated paths intuitively through augmented reality. Teaching experiments showed that non-skilled operators can make a robot move in shorter time than teaching/playback by direct teaching.
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