Testing the Usefulness of a Pan-Tilt-Zoom (PTZ) Camera in Human-Robot Interactions

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1 PROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 50th ANNUAL MEETING Testing the Usefulness of a Pan-Tilt-Zoom (PTZ) Camera in Human-Robot Interactions Curtis W. Nielsen and Michael A. Goodrich Brigham Young University Provo UT Mobile robots can be used in situations and environments that are dull, dirty, or dangerous, allowing the operator to interact with the environment from a safe and convenient distance. To improve the usefulness of these robots, pan-tilt-zoom (PTZ) cameras are often used. This paper presents a user-study comparing the usefulness of robots with stationary and PTZ cameras in a search task utilizing both a traditional interface and an augmented-virtuality 3D interface. The results from the experiments suggest that with the traditional interface the PTZ camera and stationary camera have similar performance whereas with the 3D interface the PTZ camera improves performance. INTRODUCTION Mobile robots can be used in situations and environments that are dull, dirty, or dangerous, allowing the operator to interact with the environment from a safe distance. In these situations, it is often important to present the operator visual information about various regions of the environment. One possible means for doing this is to use a pan-tilt-zoom (PTZ) camera which allows an operator to view the environment around the robot without moving the robot itself. User-studies by Yanco and Drury (2004) and Burke, Murphy, Coovert, and Riddle (2004) indicated that a significant portion of time operating a robot in search and rescue tasks was spent with the robot stationary and the operator manipulating the (PTZ) camera to observe the environment. They observed that operators used the camera to establish and maintain an awareness of the environment around the robot. However, it was observed that, despite spending significant time acquiring situation awareness, operators still expressed confusion and a sense that the information provided by the interface and the camera did not improve their understanding of the environment. This raises the question of whether it is more efficient to manipulate a PTZ camera or to simply rotate a robot with a stationary camera in the desired direction. To answer the question, an experiment that requires joint navigation and exploration was performed. The experiment is 2x2, with two camera conditions and two interface conditions. The first interface condition utilized a traditional (2D) user interface and compared performance and situation awareness when using a PTZ camera against using a stationary camera. The second interface condition implemented an augmented-virtuality (3D) interface that has been shown, in previous experiments, to support navigation tasks better than traditional interfaces (Ricks, Nielsen, and Goodrich, 2004; Nielsen and Goodrich 2006). The experiment design was between-subjects, and experiments were performed in simulation with novice participants. INTERFACE CONDITION 1 The purpose of this experiment is to use a traditional (2D) user interface to compare the usefulness of a PTZ camera and a stationary camera in a joint navigation and exploration task. The user interface presents a) video information, b) map and robot pose, and c) pan and tilt angles of the robot s camera. The map is useful for understanding the robot s location within the environment and the physical structure of the environment. In contrast, the video input provides detailed contextual information about the environment and is particularly useful for identifying objects of interest in exploration tasks. The pan-tiltzoom icons are designed to inform the user of the relative orientation of the camera with respect to the robot and, when combined with the robot icon in the map, are intended to help the operator understand from where in the environment the video input is originating. A traditional 2D interface places the various sets of information from the robot in distinct areas of the interface. The prototype of the 2D interface that was used for this experiment is shown in Figure 1. Methods Materials. For this experiment, a simulated, planar environment was designed in an attempt to

2 PROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 50th ANNUAL MEETING Figure 1. Prototype of a traditional (2D) Interface. exploit the use of a pan-tilt camera. A simple boxshaped maze with six dead-end hallways on the outside of the box and six dead-end hallways around the inside of the box was created using an in-house simulator (see Figure 2). Flags were placed at the end of eight of the twelve dead-end hallways. The main hallway had a width of two meters and the width of the dead-end hallways ranged between 1.5 and 2.5 meters. The simulated robot used for the experiment implemented a map-building algorithm developed by Konolige (2004). The map-building algorithm records the environment through a 2D planar laser range-finder positioned on the robot and parallel to the ground. This means that the operator did not know the layout of the map a priori, but discovered the map as the robot traversed the course. Participants. There were 88 novice participants in the experiment. The participants were recruited from visitors to the St. Louis Science Center between May 2 nd and May 5 th, Age and gender of participants was not recorded. Procedure. The simulated robot was controlled with a Microsoft Sidewinder steering wheel where the robot orientation was manipulated with the steering wheel and the robot forward velocity was manipulated with a pedal. The PTZ camera was panned by pressing buttons on the back of the steering wheel with the tips of the fingers. Half of the participants used the PTZ camera condition and half used the stationary camera condition. The conditions were alternated between participants throughout the experiment. Each participant operated the robot in only one condition. Participants were told that their task was to navigate the robot through the environment as quickly as possible while checking for flags in each of the dead-end corridors throughout the environment. Participants were told that when they found a flag, they were to click a button on the steering wheel to indicate that they saw the flag. Participants were told that they did not need to pick-up the flag or drive near the flag, but that they only needed to observe the flag. Due to limitations on time with each participant, operators were not allowed to practice driving the robot before the task began; these limitations were a result of using visitors to the St. Louis Science Center. Participants were advised that a good strategy was to drive the robot down the middle of the hall and when they arrived at an intersection, they should turn the robot or the camera (depending on which condition they were using) to look down the dead-end corridor without actually moving the robot into the corridor. Upon completing the instructions and answering any questions from the participant, the experiment began. Results Figure 2. The simple navigational environment. Sometimes, due to imperfections in the simulator, the robot would collide with a wall and the operator would be unable to extricate the robot. When this occurred, the experiment was recorded as incomplete and the data was discarded in the analysis of the results. With the stationary camera, 64% of the participants finished the task without getting the robot stuck in a wall and with the PTZ camera, 57% of the participants finished the task. Significance for the following results was determined with a two-sided independent means t-test. Of the participants who finished the task, those who used the PTZ camera moved the robot an average distance 41% shorter (M = 63.12m) than those who used the stationary camera (M = m) t(51) = 5.44, p < Participants with the PTZ camera also had an average velocity 39% slower (M = 0.29m/s) than those who used the stationary camera (M = 0.48m/s) t(51) = 3.95, p < The consequence of the shorter distance traveled and the slower average velocity is that the time

3 PROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 50th ANNUAL MEETING to complete the task was statistically similar for both the PTZ camera (M = 250s) and the stationary camera (M = 249s) conditions t(51) = 0.03, p = 0.97). The average times to completion were similar even though 27% less time was spent actually driving the robot with the PTZ camera (63%) than with the stationary camera (87%) t(51) = 7.01, p < With respect to the robot s proximity to obstacles in the environment, there were 46% fewer collisions with the PTZ camera (M = 6.04) than with the stationary camera (M = 11.11) t(51) = 1.75, p = and the average distance between the robot and the closest wall was statistically similar for both camera conditions (M PTZ = 0.807m, M No_PTZ = 0.797m t(51) = 0.29, p = 0.77). There are practical reasons for using simulation for the experiment, especially considering the wide variety of novice participants recruited from the St. Louis science center. Unfortunately, there is not a direct transfer of results from simulated robots to robots in the physical world; however, trends in the usefulness of the various interface paradigms (discussed later) follow observed trends with physical robots (Ricks, Nielsen, and Goodrich, 2004; Nielsen, Ricks, Goodrich, Bruemmer, Few, and Walton, 2004; Nielsen, Goodrich, and Rupper, 2005; Nielsen and Goodrich 2006). Furthermore, it is important to remember that these experiments have been limited to planar environments and the results and observations presented may not apply to non-planar environments. These results indicate that although significantly less distance is traveled by the robot with the PTZ camera, the robot also travels much slower resulting in no performance advantage with respect to the camera condition and the task completion time, however there was a marginally significant decrease in collisions. It is likely that the reason for the difference in the collisions is because it was easier to keep the robot oriented in the main hallway when the camera, not the robot, was manipulated to look down the side-hallways. When driving with the 2D interface, operators would often completely stop the robot while looking down a deadend hallway then re-center the camera in front of the robot before continuing through the environment. This would also explain why the average velocity was very slow with the PTZ camera. In contrast, the participants that used the stationary camera tended to continually drive the robot forward even when they were looking down the dead-end hallways which resulted in a higher average velocity, but also more collisions. INTERFACE CONDITION 2 The purpose of this experiment is to use an augmented-virtuality 3D user interface to compare the usefulness of a PTZ camera and a stationary camera in a joint navigation and exploration task. The user interface presents the same information as the 2D interface; however, the layout of the display varies significantly because the 3D interface renders the robot pose, map, video, and camera orientation in a virtual environment. The map information forms the basis of the virtual environment and is the same as was used with the 2D interface. The map is rendered on the floor of the virtual environment and a heuristically chosen height is given to the obstacles in the map to illustrate impassable areas. An icon of the robot is placed in the virtual environment at the at the robot s location in the map. The video representation is placed heuristically near the model of the robot so that obstacles in the video stream appear to closely match obstacles in the map. When the camera is panned from side to side, the video is rendered in the virtual environment at an angle that corresponds to the relative orientation of the camera on the physical robot. To illustrate, Figure 3 presents the video directly in front of the robot, and Figure 4 shows the camera towards the left side of the virtual robot indicating that the orientation of the camera is to the left side of the actual robot. As the robot s camera is panned, the effect is that the video in the virtual environment appears to move around the robot. The perspective from which the operator views the environment is always from a place above and behind the robot such that some map information behind the robot can be seen in the 3D interface. As the robot moves through the environment, the 3D perspective remains tethered to the robot which gives the sensation that the environment is moving instead of the robot. Methods Materials. In the second experiment, the same environment and task was used as the first experiment (see Figure 1) with the exception that a 3D interface was used instead of the traditional 2D interface. Participants. A different group of 88 novice participants took part in the second experiment than in the first experiment. The participants were recruited from visitors to the St. Louis Science Center between

4 PROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 50th ANNUAL MEETING Figure 3. The 3D augmented-virtuality interface May 2 nd and May 5 th, Age and gender of participants was not recorded. Procedure. The simulated robot was navigated with the same Microsoft Sidewinder steering wheel used with the 2D interface. Half of the participants used the PTZ camera condition and half used the stationary camera condition. The conditions were alternated between participants throughout the experiment. Each participant operated the robot in only one condition. The task, environment, and instructions for this experiment were the same as the previous experiment Results With the stationary camera, 84% of the participants finished the task without getting the robot stuck in a wall and with the PTZ camera 89% of the participants finished the task. Of those that finished the task, participants with the PTZ camera averaged a 41% shorter distance traveled by the robot t(74) = 6.83, p < along with a 21% slower average velocity t(74) = 2.94, p < In contrast to the previous experiment, the average time to completion was 13% faster with the PTZ camera (M = 157s) than with the stationary camera (M = 181s) t(74) = 2.04, p = The faster completion time was accomplished even though operators spent 23% less time actually driving the robot with the PTZ camera (M=71%) than with the stationary camera (M=92%), t(74)=7.66, p < With respect to the robot s proximity to obstacles in the environment, there were 86% fewer collisions with the PTZ camera (M = 0.56) than with the stationary camera (M = 4.11) t(74) = 3.32, p< Moreover, the robot maintained an average distance 8% farther from obstacles with the PTZ camera (M = 0.95m) than with the stationary camera (M = 0.88m) t(74) = 3.27, p < Figure 4. The 3D interface with the camera panned to the left of the robot. These results suggest that when using the 3D interface to perform a joint navigation and exploration task, the PTZ camera supports faster task completion and safer navigation than the stationary camera. It is likely that the reason for the difference in the collisions is because it was easier to keep the robot oriented in the main hallway when the camera, not the robot, was rotated to look down the side-hallways. When driving with the PTZ camera, operators would often slow the robot down while looking down a dead-end hallway then speed up again to continue through the environment. This behavior resulted in a slightly lower average velocity but a greater decrease in the distance traveled which in turn yielded faster completion times. 2D INTERFACE VS 3D INTERFACE It is also of interest that participants performed much better with the 3D interface than with the 2D interface, particularly, when using the 3D interface with the PTZ camera. The comparison between the 2D interface and the 3D interface with the stationary camera is presented next followed by the comparison between the interfaces with the PTZ camera. Stationary Camera 2D vs. 3D In conditions with the stationary camera, participants with the 3D interface finished the task 27% faster than those with the 2D interface (M 3D = 181s, M 2D = 249s t(65) = 4.59, p < 0.001) while maintaining an average velocity 40% faster (M 3D = 0.61m/s, M 2D = 0.43m/s t(65) = 1.89, p = 0.031). Operators with the 3D interface also had 63% fewer collisions (M 3D = 4.11, M 2D = 11.1 t(65) = 2.72, p < 0.01), maintained an

5 PROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 50th ANNUAL MEETING average distance 10% farther from obstacles (M 3D = 0.88m, M 2D = 0.80m t(65) = 2.61, p < 0.01), and spent 7% more time moving the robot forward (M 3D = 92%, M 2D = 87% t(65) = 3.08, p < 0.005). PTZ Camera 2D vs. 3D In conditions with the PTZ camera, the differences between the 2D interface and the 3D interface were even more pronounced. Participants with the 3D interface finished the task 37% faster than those with the 2D interface (M 3D = 157s, M 2D = 250s t(65) = 4.122, p < 0.001) while maintaining an average velocity 65% faster (M 3D =0.42m/s, M 2D =0.25m/s t(65) = 5.51, p < 0.001). Operators with the 3D interface also had, on average, 91% fewer collisions (M 3D = 0.56, M 2D = 6.04 t(65) = 3.47, p < 0.005), maintained an average distance 17% farther from obstacles (M 3D = 0.95m, M 2D = 0.81m t(65) = 5.23, p < 0.001), and spent 12% more time moving the robot forward (M 3D = 71%, M 2D = 63% t(65) = 1.91, p = 0.061). The comparison between the 2D and 3D interfaces suggest that it is easier for an operator to drive the robot with the 3D interface. We believe that this is because the 3D interface produces better awareness of the robot s surroundings by presenting the relationships between distinct sets of information, instead of only presenting the information. The observations from this experiment are similar to a number of other experiments comparing the use of a 2D interface with a 3D interface in navigation tasks (Ricks, Nielsen, and Goodrich, 2004; Nielsen and Goodrich, 2006). This experiment focused primarily on the ability to use a pan-tilt camera while moving the robot and not so much on being able to identify items of interest in the video feed. More extensive studies will have to be performed to determine whether or not the 3D interface is helpful in search tasks where the location of information is unknown. CONCLUSION The environments used for these experiments were designed to exploit the use of a PTZ camera. Despite this fact, the use of a PTZ camera with a traditional interface did not change the task completion time. In contrast, the use of a PTZ camera with the 3D interface did improve task completion time in comparison to using a stationary camera. From a design perspective, if the robot will be used in a planar environment that can be mapped using Konolige s map-building algorithm and the environment is such that a PTZ camera could be advantageous, then a 3D interface should be implemented that presents the camera orientation as it relates to the robot orientation. If a traditional interface is used for a similar task, one should not expect the time to complete the task to improve with or without a PTZ camera. In the future it would be interesting to compare the usefulness of a PTZ camera in environments that are not specifically engineered to support the use of the PTZ camera and in non-planar environments. It would also be constructive to compare interfaces and controls with experts in domains such as urban search and rescue. ACKNOWLEDGEMENTS The authors would like to thank the Army Research Lab and the Idaho National Laboratory for supporting this work. We also would like to thank Chris Roman and the St. Louis Science Center for providing an opportunity to perform the experiments. REFERENCES Burke, J. L & Murphy, R. R. & Coovert M. D. & Riddle, D. L. (2004). Moonlight in Miami: A Field Study of Human-Robot Interaction in the Context of an Urban Search and Rescue Disaster Response Training Exercise. Human-Computer Interaction 19, Konolige, K. (2004). Large-Scale Map-Making. In Proceedings of the National Conference on Artificial Intelligence (AAAI). Nielsen, C. W. & Goodrich, M. A. & Rupper, R. J. (2005). Towards Facilitating the Use of a pan-tilt camera on a mobile robot. In Proceedings of the 14 th IEEE International Workshop on Robots and Human Interactive Communication (RO-MAN). Nielsen, C. W. & Goodrich, M. A. (2006). Comparing the Usefulness of Video and Map Information in Navigation Tasks. In Proceedings of the Human-Robot Interaction Conference (HRI). Nielsen, C. W. & Ricks, B. W. & Goodrich, M. A. & Bruemmer, D. J. and Few, D. A. and Walton, M. C. (2004). Snapshots for Semantic Maps. In Proceedings of the 2004 IEEE Conference on Systems, Man, and Cybernetics (SMC). Ricks, B. W. & Nielsen, C. W. & Goodrich, M. A. (2004). Ecological Displays for robot interaction: A new perspective. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Yanco, H. A. & Drury, J.L. (2004). Where am I? Acquiring Situation Awareness Using a Remote Robot Platform. In Proceedings of the IEEE Conference on Systems, Man, and Cybernetics.

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