Robotics Commons^™

Formal Performance Guarantees For Behavior-Based Localization Missions, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang

Faculty Publications

Abstract— Localization and mapping algorithms can allow a robot to navigate well in an unknown environment. However, whether such algorithms enhance any specific robot mission is currently a matter for empirical validation. In this paper we apply our MissionLab/VIPARS mission design and verification approach to an autonomous robot mission that uses probabilistic localization software.

Two approaches to modeling probabilistic localization for verification are presented: a high-level approach, and a sample-based approach which allows run-time code to be embedded in verification. Verification and experimental validation results are presented for two different missions, each using each method, demonstrating the accuracy …

Pythagorean Combinations For Lego Robot Building., Ronald I. Greenberg

Computer Science: Faculty Publications and Other Works

This paper provides tips for LEGO robot construction involving bracing or gear meshing along a diagonal using standard Botball kits.

The Role Of Uncertainty In Categorical Perception Utilizing Statistical Learning In Robots, Nathaniel V. Powell

Graduate College Dissertations and Theses

At the heart of statistical learning lies the concept of uncertainty.

Similarly, embodied agents such as robots

and animals must likewise address uncertainty, as sensation

is always only a partial reflection of reality. This

thesis addresses the role that uncertainty can play in

a central building block of intelligence: categorization.

Cognitive agents are able to perform tasks like categorical perception

through physical interaction (active categorical perception; ACP),

or passively at a distance (distal categorical perception; DCP).

It is possible that the former scaffolds the learning of

the latter. However, it is unclear whether DCP indeed scaffolds

ACP in humans and …