What visual information is used for navigation around obstacles in a cluttered environment?

Abstract

The goal of this study was to determine what visual information is used to navigate around barriers in a cluttered terrain. Twelve traffic pylons were arranged randomly in a 4.55 x 3.15 m travel area: there were 20 different arrangements. For each arrangement, individuals (N = 6) were positioned in 1 of 3 locations on the outside border with their eyes closed: on verbal command they were instructed to open their eyes and quickly go to 1 of 2 specified goals (2 vertical posts defining a door) located on one edge of the travel area. The movement of the body was tracked using the OPTOTRAK system, with the IREDS placed on a collar worn by the subjects. Experimental data of travel path chosen were compared with those predicted by models that incorporated different types of visual information to control path trajectory. The 6 models basically use 2 different strategies for route selection: reactive control based on visual input about the obstacle encountered in the line-of-sight travel path (Model # 1) and path planning based on different visual information (Model # 2, 3, 4, 5, and 6). The models that involve path planning are grouped into 2 categories: models 2, 3, 4, and 5 need detailed geometrical configuration of the obstacles to plan a route while model 6 plans a route based on identifying and avoiding a cluster of obstacles in the travel path. Two measures were used to compare model performance with the actual travel path: the difference in area between predicted and actual travel path and the number of trials that accurately predicted the number of turns during travel. The results suggest that route selection is not based on reactive control, but does involve path planning. The model that best predicts the travel paths taken by the individuals uses visual information about cluster of obstacles and identification of safe corridors to plan a route.

A neural model of visually guided steering, obstacle avoidance, and route selection.

“…If the summed area was zero, our model would perfectly replicate the baseline trajectory. This error measurement is based on a similar measure used by Patla, Tomescu, and Ishac (2004). In addition, we also compute the maximum linear distance between the trajectory steered by our model and the baseline, which gives a worst-case measure of how far our model deviates from the correct path.…”

“…A recent study by Patla, Tomescu, and Ishac (2004) calls into question the idea that steering control is purely reactive, even in a static environment. They had subjects walk through an arrangement of 12 randomly placed traffic cones covering a 4.55 m × 3.15 m area toward a goal object.…”

Virtual proxemics: Locomotion in the presence of obstacles in large immersive projection environments

“…Heading is adapted according to the distance and the angle between the walker and stationary goals and obstacles: goals act as attractors and obstacles as repellors. Other authors suggested that path planning precedes dynamic control to navigate in a cluttered environment [14]. From a local point of view, some studies focused on the circumvention of non-human static obstacles [19].…”

Navigational strategies during fast walking: A comparison between trained athletes and non-athletes

“…The various complexities of these environmental contexts require different navigational skills implicating both the motor and cognitive aspects of the control of locomotion. Normal human behavior during obstacle circumvention is beginning to be understood in children [1], young adults [2][3][4][5], and older adults [6,7]. Understanding how trained athletes view environmental space and navigate will provide additional insights into adaptive locomotor control.…”

“…Patla et al [3] argued that considering only the next obstacle in the travel path is not the strategy used to navigate a cluttered environment. They provided some evidence that path planning is not based on detailed geometrical information about the environment, but rather on avoiding obstacle clusters in the line-of-sight travel path.…”