A number of studies have reported that distance judgments are underestimated in virtual environments (VE) when compared to those made in the real world. Studies have also reported that providing users with visual feedback in the VE improves their distance perception and made them feel more immersed in the virtual world. In this study, we investigated the effect of tactile feedback and visual manipulation of the VE on egocentric distance perception. In contrast to previous studies which have focused on task-specific and error-corrective feedback (for example, providing knowledge about the errors in distance estimations), we demonstrate that exploratory feedback is sufficient for reducing errors in distance estimation. In Experiment 1, the effects of different types of feedback (visual, tactile and visual plus tactile) on distance judgments were studied. Tactile feedback was given to participants as they explored and touched objects in a VE. Results showed that distance judgments improved in the VE regardless of the type of sensory feedback provided. In Experiment 2, we presented a real world environment to the participants and then situated them in a VE that was either a replica or an altered representation of the real world environment. Results showed that participants made significant underestimation in their distance judgments when the VE was not a replica of the physical space. We further found that providing both visual and tactile feedback did not reduce distance compression in such a situation. These results are discussed in the light of the nature of feedback provided and how assumptions about the VE may affect distance perception in virtual environments.

Complex problems, such as driving, can be solved more easily by decomposing them into smaller subproblems, solving each sub-problem, and then integrating the solutions. In the case of an autonomous vehicle, the integrated system should be able to react in real time to a changing environment and to reason about ways to achieve its goals. This paper describes the approach taken on the UMass Mobile Perception Laboratory (MPL) to integrate independent processes (each solving a particular aspect of the navigation problem) into a fully capable autonomous vehicle. >

Complex problems, such as driving, can be solved by decomposing them into simpler sub-problems, solving each sub-problem, and then integrating the solutions. In the case of an autonomous vehicle, the integrated system should be able to "react" in real time to a changing environment and to "reason" about ways to achieve its goals. This paper describes the approach taken on the UMass Mobile Perception Laboratory (MPL) to integrate independent processes (each solving a particular aspect of the navigation problem) into a fully capable autonomous vehicle.

The problem of goal-oriented navigation of an autonomous robot vehicle through a partially modeled unchanging environment which contains no unmodeled obstacles is discussed. This simplified environment provides a foundation for research in more complicated domains. Perception, planning, and execution of actions are integrated into a reactive system which reasons about landmarks that should be perceived at various stages of task execution. Perceptual servoing uses correspondences between image features and expected landmark locations to ensure proper plan execution and to maintain the relationship between the system's internal model and the environment. This system is described, and experimental results which demonstrate the efficacy of perceptual servoing are presented.>

The authors report on the system and methods used by UMass Mobile Robot Project. Model-based processing of the visual sensory data is the primary mechanism used for controlling movement of an autonomous land vehicle through the environment, measuring progress towards a given goal, and avoiding obstacles. Goal-oriented navigation takes place through a partially modeled, unchanging environment that contains no unmodeled obstacles; this simplified environment provides a foundation for research in more complicated domains. The navigation system integrates perception, planning, and execution of actions. Of particular importance is that the planning processes are reactive and reason about landmarks that should be perceived at various stages of task execution. Correspondence between image features and expected landmark locations are used at several abstraction levels to ensure proper plan execution. The system and some experiments that demonstrate the performance of its components is described.>