Toward Mobile Robots Reasoning Like Humans

Authors: Jean Oh, Arne Suppé, Felix Duvallet, Abdeslam Boularias, Luis Navarro-Serment, Martial Hebert, Anthony Stentz, Jerry Vinokurov, Oscar Romero, Christian Lebiere, Robert Dean

AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We report a summary of extensive outdoor experiments; the results suggest that a multidisciplinary approach to robotics has the potential to create competent human-robot teams.
Researcher Affiliation Collaboration Jean Oh, Arne Supp e, Felix Duvallet, Abdeslam Boularias, Luis Navarro-Serment, Martial Hebert, Anthony Stentz Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213 Jerry Vinokurov, Oscar Romero, Christian Lebiere Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213 Robert Dean General Dynamics Robotic Systems, Westminster, MD 21157
Pseudocode No The paper describes algorithms in text and provides a BNF grammar, but does not include structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide concrete access to source code for the methodology described.
Open Datasets No The paper describes using a custom dataset from a '1 km2 military training facility', but does not provide concrete access information (link, DOI, or formal citation) for this dataset.
Dataset Splits No The paper does not provide specific dataset split information (percentages, sample counts, or citations to predefined splits) needed to reproduce the data partitioning.
Hardware Specification Yes The complete end-to-end system has been integrated on Clearpath TMHusky (Clearpath ) equipped with the General Dynamics XR 3D LADAR sensor and Adonis camera (shown in Figure 1). The LADAR sensor is mounted 0.7 m above ground which creates approximately 4 m radius dead zone around the robot. A Hokuyo UTM-30LX scanning laser sensor is installed at 0.25 m for obstacle detection in the dead zone.
Software Dependencies No The paper mentions using 'PMAP with Field D*' for path planning but does not provide specific version numbers for these or other software dependencies.
Experiment Setup No The paper describes the system components and general experimental environment, but does not provide specific hyperparameter values or detailed training configurations for the learning models used (e.g., for the decision-forest classifier or the imitation learning).