Engineering topics

Hebert, Martial

Publications and source records attributed to Hebert, Martial.

6 records

DOE OSTI2017

Overview of the Carnegie Mellon University Robotics Institute DOE Trainee-ship in Environmental Management - 17493

The Robotics Institute of Carnegie Mellon University (CMU), through support from the Department of Energy (DOE), is offering an Environmental Management (EM) Trainee-ship program that is shaped by the inherent challenges in EM-related missions and seeks to cultivate the technical foundation and practical skills required to address these challenges. The trainee-ship program includes multiple new fellows per year of support (MS and/or PhD students) and builds on the existing core robotics curricula while introducing specialized topics that ensure a thorough understanding of EM-relevant concerns. The trainee-ship incorporates supervised research opportunities with CMU faculty advisors and through collaborations with DOE national labs (Pacific Northwest National Laboratory and Savannah River National Laboratory). These research opportunities aim to produce specialists who have the skills required to envision, develop, and deploy autonomous and semi-autonomous systems that directly address DOE-EM needs. Specifically, the Robotics Institute identifies two specializations in addition to the three core areas that students must master in order to develop these kinds of systems: (1) a theory perspective of how to develop autonomous systems for applications in constrained environments, and (2) a practicum that challenges students to build systems that can operate in constrained EM-relevant environments. The DOE Trainee-ship in Robotics is formulated to provide a course of study that balances theory and practice with opportunities for field evaluation in collaboration with domain partners toward addressing relevant DOE-EM challenges through robotics. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1999

Robotic Rock Classification

This report describes a three-month research program undertook jointly by the Robotics Institute at Carnegie Mellon University and Ames Research Center as part of the Ames' Joint Research Initiative (JRI.) The work was conducted at the Ames Research Center by Mr. Liam Pedersen, a graduate student in the CMU Ph.D. program in Robotics under the supervision Dr. Ted Roush at the Space Science Division of the Ames Research Center from May 15 1999 to August 15, 1999. Dr. Martial Hebert is Mr. Pedersen's research adviser at CMU and is Principal Investigator of this Grant. The goal of this project is to investigate and implement methods suitable for a robotic rover to autonomously identify rocks and minerals in its vicinity, and to statistically characterize the local geological environment. Although primary sensors for these tasks are a reflection spectrometer and color camera, the goal is to create a framework under which data from multiple sensors, and multiple readings on the same object, can be combined in a principled manner. Furthermore, it is envisioned that knowledge of the local area, either a priori or gathered by the robot, will be used to improve classification accuracy. The key results obtained during this project are: The continuation of the development of a rock classifier; development of theoretical statistical methods; development of methods for evaluating and selecting sensors; and experimentation with data mining techniques on the Ames spectral library. The results of this work are being applied at CMU, in particular in the context of the Winter 99 Antarctica expedition in which the classification techniques will be used on the Nomad robot. Conversely, the software developed based on those techniques will continue to be made available to NASA Ames and the data collected from the Nomad experiments will also be made available.

Hebert, Martial↗

NASA NTRS1991

Toward autonomous driving: The CMU Navlab. I - Perception

The Navlab project, which seeks to build an autonomous robot that can operate in a realistic environment with bad weather, bad lighting, and bad or changing roads, is discussed. The perception techniques developed for the Navlab include road-following techniques using color classification and neural nets. These are discussed with reference to three road-following systems, SCARF, YARF, and ALVINN. Three-dimensional perception using three types of terrain representation (obstacle maps, terrain feature maps, and high-resolution maps) is examined. It is noted that perception continues to be an obstacle in developing autonomous vehicles.

Thorpe, Charles↗

NASA NTRS1991

Toward autonomous driving: The CMU Navlab. II - Architecture and systems

A description is given of EDDIE, the architecture for the Navlab mobile robot which provides a toolkit for building specific systems quickly and easily. Included in the discussion are the annotated maps used by EDDIE and the Navlab's road-following system, called the Autonomous Mail Vehicle, which was built using EDDIE and its annotated maps as a basis. The contributions of the Navlab project and the lessons learned from it are examined.

Thorpe, Charles↗

NASA NTRS1989

Ambler - An autonomous rover for planetary exploration

The authors are building a prototype legged rover, called the Ambler (loosely an acronym for autonomous mobile exploration robot) and testing it on full-scale, rugged terrain of the sort that might be encountered on the Martian surface. They present an overview of their research program, focusing on locomotion, perception, planning, and control. They summarize some of the most important goals and requirements of a rover design and describe how locomotion, perception, and planning systems can satisfy these requirements. Since the program is relatively young (one year old at the time of writing) they identify issues and approaches and describe work in progress rather than report results. It is expected that many of the technologies developed will be applicable to other planetary bodies and to terrestrial concerns such as hazardous waste assessment and remediation, ocean floor exploration, and mining.

Bares, John↗

NASA NTRS1989

Perception for rugged terrain

A three-dimensional perception system for building a geometrical description of rugged terrain environments from range image data is presented with reference to the exploration of the rugged terrain of Mars. An intermediate representation consisting of an elevation map that includes an explicit representation of uncertainty and labeling of the occluded regions is proposed. The locus method used to convert range image to an elevation map is introduced, along with an uncertainty model based on this algorithm. Both the elevation map and the locus method are the basis of a terrain matching algorithm which does not assume any correspondences between range images. The two-stage algorithm consists of a feature-based matching algorithm to compute an initial transform and an iconic terrain matching algorithm to merge multiple range images into a uniform representation. Terrain modeling results on real range images of rugged terrain are presented. The algorithms considered are a fundamental part of the perception system for the Ambler, a legged locomotor.

Kweon, In SO↗