#essay

Research Report

For Efficient Navigational Search, Humans Require Full Physical Movement, but Not a Rich Visual Scene Roy A. Ruddle and Simon Lessels

School of Computing, University of Leeds, Leeds, United Kingdom

ABSTRACT—During navigation, humans combine visual

information from their surroundings with body-based in-

formation from the translational and rotational compo-

nents of their movement. Theories of navigation focus on

the role of visual and rotational body-based information,

even though experimental evidence shows they are not

sufficient for complex spatial tasks. To investigate the

contribution of all three sources of information, we asked

participants to search a computer-generated virtual room

for targets. Participants were provided with only visual

information or with visual information supplemented with

body-based information for all movement (walk group)

or rotational movement (rotate group). The walk group

performed the task with near-perfect efficiency, irrespec-

tive of whether a rich or impoverished visual scene was

provided. The visual-only and rotate groups were signifi-

cantly less efficient and frequently searched parts of the

room at least twice. These results suggest that full physical

movement plays a critical role in navigational search, but

only moderate visual detail is required.

During navigation, people update knowledge of their position

and orientation (spatial updating) to avoid becoming lost. This

process involves combining body-based information about one’s

translational and rotational movements with other sensory

information, principally visual. Theories of navigation focus

on the role of visual information and the rotational component

of movement (e.g., Gopal, Klatzky, & Smith, 1989; Mou &

McNamara, 2002), but experimental evidence highlights many

unknowns and suggests that translational body-based informa-

tion is also critical. The objective of the present study was to

determine the contribution of all three sources of information to

the ability to perform a navigational search task efficiently. 1

The environments people navigate on an everyday basis

contain visual cues that act as landmarks (Janzen & van

Turennout, 2004) and provide optic flow (Warren, Kay, Zosh,

Duchon, & Sahuc, 2001). Studies using virtual environments

(VEs) show that humans rely on landmarks when they are

available (Foo, Warren, Duchon, & Tarr, 2005), and in rich

visual scenes, basic spatial tasks such as path integration may

be performed accurately even if no body-based information is

provided (Riecke, van Veen, & Bülthoff, 2002). However, visual

information alone is not sufficient for cognitively demanding

tasks such as learning the layout of a building, as indicated by

the difficulty participants frequently have navigating VEs dis-

played on a desktop monitor (Ruddle, 2001).

Previous research on the relative importance of translational

versus rotational body-based information has been inconclu-

sive. Studies conducted using the basic spatial tasks of inter-

object pointing, path integration, and exhaustive search imply

that the rotational component of movement is critical. For ex-

ample, participants pointed more accurately and more quickly

between objects in a room if they physically turned, rather than

imagined that they turned. However, there was no significant

difference between physical and imagined translationary

movements (Presson & Montello, 1994; Rieser, 1989; see also

Mou, McNamara, Valiquette, & Rump, 2004). In another study,

Address correspondence to Roy A. Ruddle, School of Computing, University of Leeds, Leeds, LS2 9JT, United Kingdom, e-mail: royr@ comp.leeds.ac.uk.

1 In navigational search, a person has to travel through a space to search it. By

contrast, visual search generally involves eye movements and a single display, and gaze-based search involves head and eye movements from a fixed position.

PSYCHOLOGICAL SCIENCE

460 Volume 17—Number 6Copyright r 2006 Association for Psychological Science

path integration was performed accurately in an immersive VE 2

that provided optic flow for all movement but body-based infor-

mation only for rotational movement. By contrast, participants

made large errors when they were provided no body-based in-

formation in a VE, were provided only a verbal description, or

observed someone else walking the path (Klatzky, Loomis, Beall,

Chance, & Golledge, 1998; see also Avraamides, Klatzky,

Loomis, & Golledge, 2004). Finally, participants took substan-

tially longer to exhaustively search a room from a fixed position

(gaze-based search) if the direction of view was controlled by

hand rather than head movements (Pausch, Proffitt, & Williams,

1997). The researchers attributed the difference in efficiency to

the fact that parts of the room were searched more than once with

hand movements, but not with head movements. In everyday life,

the use of head musculature to look around is well practiced.

In more complex spatial tasks involving estimating the di-

rection to targets along a route, full (i.e., translational and ro-

tational) body-based information appears to hold advantages

over rotational information on its own. In one study (Chance,

Gaunet, Beall, & Loomis, 1998), participants were divided into

three groups that all used an immersive VE but differed in the

body-based information that was provided: (a) none (visual-only

group), (b) rotational information (participants physically turned

but controlled forward speed using a joystick), and (c) rotational

and translational information (participants literally walked

through the VE while physically situated in a large empty room).

Participants who walked estimated directions significantly more

accurately than those in the visual-only group. Performance of

the rotation-only group was not significantly different from that

of either of the other groups. In another study, participants either

walked a route while viewing video images on a head-mounted

display (HMD) or viewed recorded video while remaining

physically stationary in the laboratory (Waller, Loomis, & Haun,

2004). Again, participants who walked estimated directions

significantly more accurately than those who were provided with

no body-based information.

Further evidence concerning the minimal contribution made

by rotational body-based information comes from studies in

which participants learned the layout of a large-scale environ-

ment (Ruddle, Payne, & Jones, 1999; Ruddle & Péruch, 2004).

In each study, they navigated one environment in an immersive

VE (rotational body-based information provided) and another in

a desktop VE (only visual information provided). The accuracy

of their route knowledge (distance traveled between specific

targets) did not differ between the immersive and desktop VEs,

and there was no consistent difference in survey knowledge

across the studies (participants’ estimates of relative straight-

line distance were more accurate in an immersive VE than a

desktop VE in the 1999 study, but less accurate in an immersive

VE than a desktop VE in the 2004 study; in neither study was

there a significant difference between the accuracy of partici-

pants’ direction estimates in immersive VEs and their accuracy

in desktop VEs).

To investigate the importance of visual information and ro-

tational and translational body-based information in complex

spatial tasks, we performed an experiment in which participants

searched a room-sized space for eight targets that were randomly

placed in 16 explicitly identified possible locations.

MAIN EXPERIMENT

The experiment was conducted within a photorealistic virtual

model of our laboratory. A between-participants design was

used, with each participant randomly assigned to one of three

groups that differed in the type of body-based information pro-

vided and the visual display (see Table 1).

Method

Participants

Thirty individuals (14 female) with a mean age of 24 years (SD 5

3.4) took part. All gave informed consent and were paid an

honorarium for their participation. The study was approved by

the Ethics Committee, Institute of Psychological Sciences,

University of Leeds, United Kingdom.

Materials

The photorealistic VE model was constructed using measure-

ments of the laboratory’s geometry (see Fig. 1a) and photographs

of the interior. Added to the model were 33 identical cylinders

and 16 identical boxes (see Fig. 1b) that, in each trial, were

placed on top of cylinders chosen at random. Half of the boxes

contained a red target, and the others were decoys. In each trial,

participants were asked to travel around the VE until they had

found the eight targets, pressing either a button on a 3-D mouse

(walk and rotate groups) or a key on a keyboard (visual-only

group) to raise and lower a box’s lid to see whether a target was

inside. The VE software prevented more than one box lid from

being raised at any given moment in time. Another button or key

was pressed to indicate a target had been found, causing it to

turn blue. The VE was rendered by an SGI Onyx4 graphics

TABLE 1

Body-Based and Visual Information Provided to Each Group of

Participants

Group name

Body-based information

Visual informationTranslation Rotation

Walk Yes Yes Stereo head-mounted display

Rotate No Yes Stereo head-mounted display

Visual-only No No Monitor (not stereo)

2 An immersive VE is one in which a participant has (almost) no view of the

outside world. This is most commonly achieved by presenting the VE on a head- mounted display, which obscures the outside world and leaves the participant visually ‘‘immersed’’ in the VE.

Volume 17—Number 6 461

Roy A. Ruddle and Simon Lessels

workstation at 60 frames/s, with overall system latency of ap-

proximately 50 ms.

Participants in the walk group physically walked around the

laboratory while viewing the corresponding virtual model on an

HMD (481 � 361 field of view; 100% binocular overlap; see Fig. 1d). Participants in the rotate group stood in one place,

viewed the VE on the HMD, and achieved movement by phys-

ically rotating to change their orientation in the VE, but held

down a button on the 3-D mouse to change position (they moved

forward in the direction they were facing). Thus, the setups of

these two groups were similar to those used by Chance et al.

(1998). Participants in the visual-only group viewed the VE on a

21-in. monitor and used the mouse and keyboard to change

position and orientation. The graphical field of view (481 � 391) was similar to the angle subtended by the monitor from a normal

viewing distance (600 mm).

Procedure

Each participant in the visual-only group performed four prac-

tice trials to become familiar with the interface controls and

search task, and then performed four test trials. Participants in

the walk and rotate groups completed two practice trials using

the same system as the visual-only group, and then two more

practice trials and four test trials using the type of movement

relevant to their group (walk or rotate). This procedure allowed

participants’ initial familiarization with the task to take place

Fig. 1. The experimental setup: (a) plan view of the physical laboratory, showing the location of the virtual cylinders; (b) photorealistic virtual environment (VE) used in the main experiment; (c) visually impoverished VE used in the supplementary experiment; and (d) person standing in the position used to generate views (b) and (c), wearing the head-mounted display.

462 Volume 17—Number 6

Full Physical Movement

while they sat in front of a monitor, rather than while they wore

an HMD that obscured the experimenter.

Results and Discussion

Our interest centered on the efficiency of participants’searches, as

indexed by the amount of the environment they visited twice (or

more) before successfully completing a trial. The dependent var-

iable used to measure search efficiency was the number of target

and decoy boxes that were checked more than once during a trial.

A ‘‘perfect’’ search was one in which no boxes were rechecked.

The rotate and visual-only groups performed 45% and 43%,

respectively, of their trials perfectly, and in 10% of trials re-

checked at least half of the boxes. The walk group performed

90% of trials perfectly, a level of performance comparable to that

observed in an earlier study in which participants performed a

similar task in the real world with either a normal field of view

(93% perfect) or while wearing goggles that limited the field of

view to 201 � 161 (87% perfect; Lessels & Ruddle, 2005). The distribution of the search-efficiency data was normalized

using a square root transformation. A 3 � 2 � 4 (Movement � Gender � Trial) mixed factorial analysis of variance (ANOVA) showed a significant effect of movement on search efficiency,

F(2, 24) 5 9.74, prep 5 .99, Zp 2 ¼ :45 (see Fig. 2). Bonferroni

post hoc tests showed that participants in the walk group re-

checked significantly fewer boxes than those in the rotate (prep 5

.97) and visual-only (prep 5 .99) groups; these latter two groups

were equivalent. The main effects of gender and trial were not

significant, and there were no significant interactions.

These results show that both translational body-based infor-

mation and rotational body-based information were necessary

for participants to efficiently search a room-sized space for

targets. When translational information was not provided, per-

formance was similar to that observed when participants had to

search using just visual information.

In previous research, participants pointed to targets along a

route significantly more accurately when full body-based in-

formation was added to visual information (Chance et al., 1998;

Waller et al., 2004). However, never before has experimental

evidence demonstrated the importance of the translational

component of body-based information over and above the rota-

tional component. In doing so, our findings help explain why

participants in previous studies learned the layouts of buildings

at a similar rate regardless of whether or not they received ro-

tational body-based information (Ruddle et al., 1999; Ruddle &

Péruch, 2004).

The visual environment used in the main experiment

contained a rather homogeneous region of cylinders that was

searched, together with many salient surrounding features (e.g.,

door, cupboards, and computers; see Fig. 1) that may have

helped participants maintain their orientation and, therefore,

may have helped them identify the parts of the cylinder region

that had or had not been searched. To investigate whether rich

visual information, as well as full body-based information, was

required, we conducted a supplementary experiment using an

impoverished VE model.

SUPPLEMENTARY EXPERIMENT

For the supplementary experiment, we replaced the photoreal-

istic VE model with one that contained only the cylinders, boxes,

and targets, plus four gray walls (see Fig. 1c). This impoverished

environment contained far less visual information for a partic-

ipant to use. Twenty new participants (12 female) with a mean

age of 22 years (SD 5 4.0) were recruited and randomly assigned

to two groups. Half of these participants walked around the

impoverished VE, and the others moved using mouse and key-

board (visual-only group).

Once again, search efficiency was measured by counting the

number of target or decoy boxes that were checked more than

once during a trial. The percentages of perfect trials were similar

to those in the main experiment (45% for the visual-only group,

90% for the walk group). The distribution of the search-effi-

ciency data was normalized using a square root transformation.

A 2 � 2 � 4 (Movement � Gender � Trial) ANOVA showed that the walk group rechecked significantly fewer boxes than the

visual-only group, F(1, 16) 5 15.66, prep 5 .99, Zp 2 ¼ :49 (see

Fig. 2). A second ANOVA showed no difference between par-

ticipants who used the walking interface in the impoverished

and photorealistic environments, F(1, 16) < 0.01, prep 5 .50,

Fig. 2. Search efficiency, defined as the mean of the square root of the number of target and decoy boxes rechecked in each trial, as a function of movement condition and visual environment. Error bars indicate stan- dard errors.

Volume 17—Number 6 463

Roy A. Ruddle and Simon Lessels

Zp 2 < :01. No other main effects or interactions were significant

in either analysis.

This supplementary experiment showed that rich visual in-

formation was not required for efficient searching if full body-

based information was provided.

GENERAL DISCUSSION

Our results demonstrate the critical role that body-based in-

formation from full physical movement (translation and rotation)

plays in navigational search. In marked contrast, for basic

spatial tasks rotational body-based information is sufficient.

This difference in the importance of translational information is

likely due to the higher cognitive demand of our task. In the

studies of path integration, interobject pointing, and route fol-

lowing, participants were instructed to make particular move-

ments, so they could devote their cognitive resources to updating

their position relative to objects in the environment. Our task

was a form of foraging with simultaneous target encounters

(Stephens & Krebs, 1986). Participants had to plan where to

travel, detect every target in their vicinity as they moved, and

remember where they had been. Full physical movement al-

lowed detection and position updating to be largely automated,

so the information necessary for ongoing planning during a

search (‘‘embodied cognition’’—see Wilson, 2002) was made

available at minimal cognitive cost.

Our results also show that if full body-based information is

provided, then a rich visual scene is not necessary for efficient

searching, thus extending to a more complex setting the findings

from path integration (Kearns, Warren, Duchon, & Tarr, 2002)

and obstacle avoidance (Loomis, Beall, Macuga, Kelly, & Smith,

2006).

The present research raises important issues in three distinct

areas. First, theoretical models of human navigation and spatial

memory tend to focus on the rotational aspects of movement,

concentrating, for example, on the role of rotation in defining the

frames of reference used to accomplish spatial tasks (e.g., Mou &

McNamara, 2002). It is now clear that these theories also need to

take into account the role of body translation in spatial updating.

Second, some researchers have raised concerns that many

VEs used to investigate navigation lack the visual complexity

and richness of a real environment and, therefore, are not eco-

logically valid (Spiers & Maguire, 2004). However, we suggest

that a far greater concern is the widespread use of desktop en-

vironments to study navigation, because these provide none of

the body-based information that has been shown to be essential.

Third, our navigational task is the most complex one to date in

which performance in a VE was comparable to performance in

the real world. This study represents a notable step toward the

creation of a virtual reality and highlights the need for renewed

efforts to develop effective technologies that allow people to

‘‘walk’’ through large virtual spaces (e.g., Iwata, Yano, Fuku-

shima, & Noma, 2005). Success would have widespread impact

on applications in training (Farrell et al., 2003), as well as on the

use of VEs as simulators for studying navigation in realistic

settings (e.g., Tarr & Warren, 2002).

Acknowledgments—This work was supported by Grant GR/

R55818/01 from the Engineering and Physical Sciences Re-

search Council. We also thank J. Loomis, A. Ruppertsberg, J.

Cutting, and an anonymous reviewer for insightful comments

about drafts of this article.

REFERENCES

Avraamides, M.N., Klatzky, R.L., Loomis, J.M., & Golledge, R.G.

(2004). Use of cognitive versus perceptual heading during imag-

ined locomotion depends on the response mode. Psychological Science, 15, 403–408.

Chance, S.S., Gaunet, F., Beall, A.C., & Loomis, J.M. (1998). Loco-

motion mode affects the updating of objects encountered during

travel: The contribution of vestibular and proprioceptive inputs to

path integration. Presence: Teleoperators and Virtual Environ- ments, 7, 168–178.

Farrell, M.J., Arnold, P., Pettifer, S., Adams, J., Graham, T., & Mac-

Manamon, M. (2003). Transfer of route learning from virtual to real

environments. Journal of Experimental Psychology: Applied, 9, 219–227.

Foo, P., Warren, W.H., Duchon, A., & Tarr, M.J. (2005). Do humans

integrate routes into a cognitive map? Map- versus landmark-

based navigation of novel shortcuts. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31, 195–215.

Gopal, S., Klatzky, R.L., & Smith, T.R. (1989). NAVIGATOR: A psy-

chologically based model of environmental learning through

navigation. Journal of Environmental Psychology, 9, 309–331. Iwata, H., Yano, H., Fukushima, H., & Noma, H. (2005). CirculaFloor:

A locomotion interface using circulation of movable tiles. In

Proceedings of the IEEE Virtual Reality Conference VR’05 (pp. 223–230). Los Alamitos, CA: IEEE.

Janzen, G., & van Turennout, M. (2004). Selective neural representa-

tion of objects relevant for navigation. Nature Neuroscience, 7, 673–677.

Kearns, M.J., Warren, W.H., Duchon, A.P., & Tarr, M.J. (2002). Path

integration from optic flow and body senses in a homing task.

Perception, 31, 349–374. Klatzky, R.L., Loomis, J.M., Beall, A.C., Chance, S.S., & Golledge, R.G.

(1998). Spatial updating of self-position and orientation during

real, imagined, and virtual locomotion. Psychological Science, 9, 293–298.

Lessels, S., & Ruddle, R.A. (2005). Movement around real and virtual

cluttered environments. Presence: Teleoperators and Virtual En- vironments, 14, 580–596.

Loomis, J.M., Beall, A.C., Macuga, K.L., Kelly, J.W., & Smith, R.S.

(2006). Visual control of action without retinal optic flow. Psy- chological Science, 17, 214–221.

Mou, W., & McNamara, T.P. (2002). Intrinsic frames of reference in

spatial memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 162–170.

Mou, W., McNamara, T.P., Valiquette, C.M., & Rump, B. (2004). Allo-

centric and egocentric updating of spatial memories. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30, 142–157.

464 Volume 17—Number 6

Full Physical Movement

Pausch, R., Proffitt, D., & Williams, G. (1997). Quantifying immersion

in virtual reality. In Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH ’97) (pp. 13–18). New York: Association for Computing Machinery.

Presson, C.C., & Montello, D.R. (1994). Updating after rotational and

translational body movements: Coordinate structure of perspec-

tive space. Perception, 23, 1447–1455. Riecke, B.E., van Veen, H.A.H.C., & Bülthoff, H.H. (2002). Visual

homing is possible without landmarks: A path integration study in

virtual reality. Presence: Teleoperators and Virtual Environments, 11, 443–473.

Rieser, J.J. (1989). Access to knowledge of spatial structure at novel

points of observation. Journal of Experimental Psychology: Learn- ing, Memory, and Cognition, 15, 1157–1165.

Ruddle, R.A. (2001). Navigation: Am I really lost or virtually there? In

D. Harris (Ed.), Engineering psychology and cognitive ergonomics (Vol. 6, pp. 135–142). Burlington, VT: Ashgate.

Ruddle, R.A., Payne, S.J., & Jones, D.M. (1999). Navigating large-scale

virtual environments: What differences occur between helmet-

mounted and desk-top displays? Presence: Teleoperators and Vir- tual Environments, 8, 157–168.

Ruddle, R.A., & Péruch, P. (2004). Effects of proprioceptive feedback

and environmental characteristics on spatial learning in virtual

environments. International Journal of Human-Computer Studies, 60, 299–326.

Spiers, H.J., & Maguire, E.A. (2004). A ‘landmark’ study on the neural

basis of navigation. Nature Neuroscience, 7, 572–574. Stephens, D.W., & Krebs, J.R. (1986). Foraging theory. Princeton, NJ:

Princeton University.

Tarr, M.J., & Warren, W.H. (2002). Virtual reality in behavioral neu-

roscience and beyond. Nature Neuroscience, 5, 1089–1092. Waller, D., Loomis, J.M., & Haun, D.B.M. (2004). Body-based senses

enhance knowledge of directions in large-scale environments.

Psychonomic Bulletin & Review, 11, 157–163. Warren, W.H., Kay, B.A., Zosh, W.D., Duchon, A.P., & Sahuc, S. (2001).

Optic flow is used to control human walking. Nature Neuroscience, 4, 213–216.

Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9, 625–636.

(RECEIVED 7/27/05; REVISION ACCEPTED 11/15/05; FINAL MATERIALS RECEIVED 12/5/05)

Volume 17—Number 6 465

Roy A. Ruddle and Simon Lessels