Using Real Objects for Interaction Tasks in Immersive Virtual Environments
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1 Using Objects for Interaction Tasks in Immersive Virtual Environments Andy Boud, Dr. VR Solutions Pty. Ltd. Abstract. The use of immersive virtual environments for industrial applications has now reached maturity in a number of areas including oil and gas exploration and the visualisation of complex scientific data sets. However, there are still a number of applications which benefit greatly from the use of three-dimensional immersive virtual environments, but technological limitations, user interaction techniques and cost still prohibit general acceptance of this technology for use as an everyday tool. This paper presents the use of instrumented objects in immersive virtual environments to aid haptic feedback for applications including, but not limited to, off-line robot programming, assembly planning, assembly training and teleoperation of remotely operated vehicles. The paper describes the motivation behind the use of instrumented objects for manipulation tasks in immersive virtual environments and presents findings from previous research which compares interaction tasks between a mouse and keyboard, six degree of freedom interaction device, an instrumented object and the real task. Findings show that using an instrumented object for object manipulation offers significantly improved performance over conventional interaction techniques. Implications of this approach including the advantages and limitations are discussed. The paper presents this work in an application context of programming robotic devices via immersive virtual environments and discusses the benefits of this approach and identifies where similar successes can be achieved. 1. INTRODUCTION The emergence of Virtual ity (VR) technology has been widely documented in popular publications in many media forms, from television programs and news articles to Hollywood films. The term VR has been used to depict and describe encompassing ways to interact with almost lifelike computer generated data. Whilst the possibilities certainly present great potential, we are still a long way from achieving a truly virtual reality. However, there are significant advantages where VR technology can be applied to complex areas of visual analysis. Typically, benefits are obtained when highly complex three-dimensional information needs to be presented, understood and interacted with in an intuitive way. Whilst this paper does not seek to present these application areas, it does highlight a number of advantages where immersive virtual environments are beneficial to industry. This paper presents the investigation and development of an interaction technique where instrumented real objects are used to conduct three-dimensional (3D) manipulation tasks in a 3D immersive environment. 2. BACKGROUND Research was conducted to investigate current problems associated with programming robotic devices for manufacturing applications and to develop new approaches to overcome existing limitations of current methods. 2.1 Robot Programming Robot programming tasks are generally classified into two separate categories; on-line and off-line. On-line methods require the programmer to have direct access to the robot and the associated work environment. Using this approach, a robot is manipulated to a position, the position is stored and this process is repeated until several positions and actions have been defined to form the basis of a robot program. Once all of the desired positions and tasks have been saved, the operations are then executed in a sequence of stored actions in program form. The on-line method is considered to be highly intuitive as the operator has direct access to the robot and the associated operating environment during programming and directly manipulates the robot to specified location. However, high downtimes of the robot and, additionally, the entire production line can be encountered due to the use of the robot during the programming process. As manufacturing trends have moved towards a more flexible environment, with increased emphasis placed on cellular manufacturing concepts, the method of robot programming employed has become increasingly important to achieve improved productivity. These requirements have lead to the development of off-line programming methods where a robot program is generated whilst the robot is in operation. The off-line method generally requires a higher operative skill level as sophisticated software packages are usually employed for this task.
2 The motivation for the initial research was to develop a method of off-line robot programming, requiring a low operative skill level whilst also being intuitive to achieve maximum productivity of the manufacturing environment. 2.2 VR technology To meet the demanding requirements for an improved robot programming method, VR technology was considered as a medium to obtain the intuitiveness of programming achieved with on-line methods, whilst also accessing the benefits of performing the programming task off-line. The actual sequence of actions performed by a robot is essentially a 3D manipulation of 3D parts in a 3D space. This highlights the applicability of VR as an enabling technology to analyse and overcome the limitations in current robot programming methods. VR combines a number of different technologies to enable real time interaction with a computer generated environment. Brooks [1] names four such areas that are crucial to the successful adoption of VR: the visual (and aural and haptic) displays that immerse the user in a virtual world that block out contradictory sensory impressions from the real world; the graphics rendering systems that generate, at 20 to 30 frames per second, the ever changing images; the tracking system that continually reports the position and orientation of the user s head and limbs; and the database construction and maintenance system for building and maintaining detailed realistic models of the virtual world (p. 16). The predominant sense that presents a virtual environment (VE) to a user is visual. However, sensory information can be enhanced with the addition of haptic, auditory and olfactory feedback. In this research, visual feedback is the dominant sensory modality with the inclusion of haptic information for certain interaction techniques. 2.3 Haptic Feedback Previous work has highlighted the lack of haptic feedback when interacting with objects in a VE [2]. However, very few immersive interaction techniques employ any form of sensory feedback other than visual, mainly relying on other indications such as proprioception [3]. The human haptic system is described by Ellis et al [4] as the sensory system which includes proprioceptive sensing of muscle/tendon states as well as tactile sensing of skin deformation (p. 321). Hence, haptic feedback is the term generally used to encompass tactile, force, and kinesthetic feedback. Tactile feedback generates a sense of touch to the skin of the user, force feedback provides a sensation of weight or resistance to an object, and kinesthetic feedback provides a sensation of muscles and tendon activity through body movements. One of the main reasons we have not seen a device fully capable of supporting a haptic system is the complicated structure of the underlying physiology of these processes. Wilson [5] indicates that a creation of a perfect representation of tactile and force feedback is unlikely to be technically possible (p. 1068). A number of haptic devices have been developed which do offer a good degree of tactile feedback, but fail to provide significant force feedback, and vice versa. The selection of a haptic feedback device is therefore dependent upon the application and the actual task being performed. For certain applications, using just a force feedback device may not provide all the necessary haptic information. However, if a device is required to provide more encompassing haptic information, then force, tactile and kinaesthetic feedback is required for each of these modalities. This paper presents the use of real objects, referred to as instrumented objects (IO), which are tracked in a virtual environment. The advantage of developing a technique where a real object can be manipulated is that the user will achieve tactile, force and kinaesthic feedback from one device, hence achieving full haptic feedback from an interaction device. This paper presents results of previous experimentation undertaken to test this approach for a user interaction technique in VEs. 3. PLATFORM SELECTION EXPERIMENT Before designing and implementing a VR interface, it is important to investigate the optimal VR platform for a particular task. For robot programming applications, object manipulation occurs in 3D, hence an initial study investigated two object manipulation tasks (location I (2D), and location II (3D)) to determine the optimal VR platform from Desktop (standard monitor, with mouse), Desktop + Stereoscopic (standard monitor with stereo viewing enabled with stereoscopic eyewear and a mouse) and Immersive (head mounted display (HMD) and position tracked 3D mouse). Results indicated that the Desktop condition offered the lowest task completion times for location I, while the Immersive condition offered superior task completion times for location II. These findings can be attributed to task, where in location I a 2D planar interaction device (mouse) is used for a 2D manipulation task, whereas for location II a 3D mouse was used for a 3D manipulation task. Statistical analysis undertaken showed that the Immersive condition offers significantly improved performance [F(2,56)= 13.38, p<0.0001] when comparing both 2D and 3D manipulation tasks. Participants were also asked to complete a questionnaire where feedback indicated that the Immersive condition was the preferred platform when performing 3D manipulation tasks.
3 4. IO EXPERIMENTATION 4.1 Classification of Visual and Haptic Feedback A simple classification of visual and haptic feedback can be made on the basis of whether the domain of the feedback is real or virtual, where each is represented by a cell in the matrix. Table 1: Feedback Classification Visual Feedback Virtual Haptic A D Feedback Virtual B C Reading counter-clockwise from A, cell A represents real-task performance, cell B represents telemanipulation (often performed with visual display), cell C represents conventional VR without haptic feedback, and cell D represents real haptic augmentation of a visually displayed VE. Our interest is twofold, (i) to compare the effects of these different configurations on user performance, and (ii) to examine D in more detail. Hand [6] states providing feedback by manipulating physical input devices which closely correspond to virtual objects is an important step towards bridging the gap between knowing what we want to do and knowing how to do it (p. 272). Examples of research into these physical input devices include Murakami s and Nakakima s [7] use of deformable shapes to interact with virtual space; Hinckley s et al. [8] use of an instrumented cutting plane to inspect brain scans; and Taylor [9] who has investigated the use of surrogate objects for object manipulation in VEs using a robotlike device. Thus, the idea of considering real objects to manipulate virtual representations is receiving growing support. 4.2 Experimental Background Previous work e.g. Gupta et al. [10],[11] investigates part handling and insertion performance times for a peg in hole task and compares cell A with cell C in Table 1. The task is performed using either a PHANTOM force feedback device from Sensable Technologies, Inc. to manipulate a virtual peg into a hole, or a physical peg to be inserted into a hole, where the real and simulated tasks have the same size, weight, frictional characteristics, and index of difficulty as defined by Fitts law [12]. The results indicated that performance times in the multimodal VE were twice as long as the real world, whereas trends in the variation in assembly times with parameters such as friction, chamfer, clearance, and handling distances were the same. However, the authors noted that the provision of force feedback tended to improve performance (assembly completion times were found to increase by a factor of 1.3 with the absence of force feedback), particularly in the insertion phase. While the authors note several possible explanations for the differences in performance, we will draw upon two for our discussion: (i) dissociation between visual and haptic displays meant that it was difficult for the users to match physical actions to space; (ii) object manipulation using the PHANTOM differed to that using the real object, i.e., the point of contact at fingertip differed in the two modes. This research investigates matching visual and haptic information to allow object manipulation to follow activity as used in real tasks. Richard et al. [13] have conducted studies using the Rutgers Master feedback device for object manipulation performance in VEs. With the provision of haptic feedback, they found that task performance was improved by 50%, and learning times were reduced by 50%. This experiment compares cells A, C and D in order to determine the utility of D, i.e. to compare real and VE performance with that of a hybrid haptic augmented VR (see Figure 1). 4.3 Participants For this experiment, 4 participants were selected from the School of Manufacturing and Mechanical Engineering at the University of Birmingham. All participants were male and had over 6 months experience of VR applications. [NOTE: Only 4 participants were selected to minimise any difference in learning effects, as it was anticipated that even extensive training could not bring additional participants up to the same level of experience within a short space of time.] 4.4 Equipment In this study, IOs are employed as the interaction devices for VR. The objects are wooden discs fitted with a magnetic position sensor, which can be used (in much the same fashion as a 3D mouse), to move a graphical representation of the object in a VE. In this way, the properties of real objects will be used for human-computer interaction to aid haptic feedback for object manipulation tasks. Experimental conditions were conducted on a Silicon Graphics Indigo 2 Maximum Impact workstation, running Division s dvity (version 5) VR software. The input device employed was either a conventional mouse or a 3D mouse. Viewing devices used were a 21 monitor and a Virtual Research Vr4 HMD. A Polhemus Fastrak magnetic tracking system was used for the 2D and 3D conditions to determine the position and orientation of the HMD and 3D mouse. (NOTE: The use of magnetic sensors incurs additional lag times than encountered for the 2D condition. There was no adjustment for this additional time in the 3D and IO results.) The geometry of the VE was constructed using 3D Studio Max R2, and consisted of approximately 7K polygons and 3Mb of texture memory.
4 4.5 The Task Figure 1: Object Manipulation in VEs The Tower of Hanoi experiment was selected as it requires a number of movements in a defined sequence of actions. It consists of three rings of different sizes, which have to be sequentially stacked on three pegs. To start, all 3 rings are placed in order, from the largest ring at the bottom, to the smallest ring at the top. The puzzle requires the participant to move the rings one at a time so that they end up in the same order, but on a different peg. One of the rules of the puzzle is that a larger ring is not allowed to be placed on top of a smaller ring. Although this task sounds fairly simple, there is only one correct sequence of movement to complete the task, and this requires seven different ring movements. Each condition was selected at random and completed 10 times under five conditions; immersive VR using a 3D mouse (C); immersive VR and IOs (D); desktop VR and conventional 2D mouse (C); real environment with real objects (A), and the real environment, but blindfolded. 4.6 Results of the Tower of Hanoi Problem Total time (s) D 3D IO Blindfold Figure 2: Mean Performance Times for the different conditions The total time to solve the Tower of Hanoi problem, using seven steps, for the different devices is shown in Figure 2. A one-way Analysis of Variance for total time, with five levels (2D mouse, 3D mouse, IO, real and blindfold interaction), was calculated. The results show a significant main effect across levels [F(4,12) = 35.6, p<0.0001]. Post-hoc Tukey tests (at p<0.05) indicate significant differences between the conditions indicated by a tick as shown in Table 3. Additional post-hoc Tukey tests (at p<0.005) did not reveal any differences between the conditions that are indicated by a cross. Table 3: Significant Interactions indicated by Tukey Tests 3D IO Blindfold 2D X 3D IO X Figure 3 shows the movement path for one participant moving the smallest IO. A normal video frame rate is used, i.e. each mark represents 1/25 th sec. It is noticeable that the real condition (shown by black circles) has a far smoother progression of movement, and that the IO condition has lengthy delays on and off the pole (See Table 2). Furthermore, it is important to note the collision on the left hand pole as the IO bumps into it and is guided down by the user. IO Figure 3: Movement Path for the Tower of Hanoi Table 2: Movement analysis of the small ring in a real and VE with an IO From Left Peg 56 Environment VR with IO 16 Left to Right Peg X Place on Right Peg Discussion of the IO Experimentation This experimentation has investigated whether, with the introduction of IOs for object manipulation tasks,
5 performance times could be improved with the provision of tactile, force and kinesthetic feedback, over 2D and 3D interaction techniques. It has demonstrated superior performance when using IOs. Reports from participants suggest a possible explanation of this benefit as follows: when using the 3D mouse, performance is visually guided, i.e., the objects are being driven across the screen. With the IO, visual feedback plays less of a role, with tactile feedback provided by the object, allowing movement to be aimed at the target. The use of IOs as an input device for object manipulation tasks conducted in personal space therefore offers significantly improved performance in comparison to other VR conditions investigated. However, although the experimentation has shown that the addition of haptic feedback improves task completion times, the application of IOs is currently limited where mapping is 1:1, due to the synchronisation between the visual and real object. 4.8 Summary This paper discusses the use of an IO for tasks that are conducted in personal space using immersive virtual environments, providing the user with encompassing haptic feedback. Results indicated that there was a significant effect for the interaction technique [F(4,12)=35.6, p<000.1] and Post-hoc Tukey tests indicated that the IO provided significantly improved task completion times compared to the 2D and 3D condition. REFERENCES 1. Brooks, F.P., (1999) What s About Virtual ity?, IEEE Computer Graphics and Applications, Nov/Dec, pp Burdea, G.C., (1996), Force and Touch Feedback for Virtual ity John Wiley : New York. 3. Mine, M.R., Brooks, F.P., Sequin, C.H.,, (1997) Moving Objects in Space: Exploiting Proprioception in Virtual-Environment Interaction, Proceedings of the ACM SIGGRAPH 97 Conference on Computer Graphics, pp Ellis, R.E., Ismaeil, O.M., & Lipsett, M.G. (1996) Design and evaluation of a high-performance haptic interface, Robotica, 14, Wilson, J.R., (1997) Virtual environments and ergonomics: needs and opportunities, Ergonomics, Vol. 40, No. 10, pp Hand, C. (1997) A survey of 3D interaction techniques, Computer Graphics Forum, 5, Murakami, T., & Nakakima, N. (1994) Direct and intuitive input devices for 3D shape deformation, CHI 94, , New York: ACM Press. 8. Hinckley, K., Pausch, R., Goble, J.C., & Kessell, N.F. (1994) Passive real-world interface props for neurosurgical visualization, CHI 94, , New York: ACM Press. 9. Taylor, P. (1995) Tactile and kinaesthetic feedback in virtual environments, Transactions of the Institute of Measurement and Control, 17(5), Gupta, R., Sheridan, T., & Whitney D. (1997(a)) Experiments Using Multimodal Virtual Environments in Design for Assembly Analysis, Presence, 6(3), Gupta, R., Whitney, D., & Zeltzer, D. (1997(b)) Prototyping and Design for Assembly analysis using multimodal virtual environments, Computer-Aided Design, 29(8), Fitts, P.M. (1954) The information capacity of the human motor system in controlling the amplitude of movement, Journal of Experimental Psychology, 47, Richard, P., Birebent, G., Coiffet, P., Burdea, G., Gomez, D., Langrana, N., (1996), Effects of Frame Rate and Force Feedback on Virtual Object Manipulation, PRESENCE, Vol. 5, No. 1, pp
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