7,486 research outputs found
A perception and manipulation system for collecting rock samples
An important part of a planetary exploration mission is to collect and analyze surface samples. As part of the Carnegie Mellon University Ambler Project, researchers are investigating techniques for collecting samples using a robot arm and a range sensor. The aim of this work is to make the sample collection operation fully autonomous. Described here are the components of the experimental system, including a perception module that extracts objects of interest from range images and produces models of their shapes, and a manipulation module that enables the system to pick up the objects identified by the perception module. The system was tested on a small testbed using natural terrain
Video Guidance, Landing, and Imaging system (VGLIS) for space missions
The feasibility of an autonomous video guidance system that is capable of observing a planetary surface during terminal descent and selecting the most acceptable landing site was demonstrated. The system was breadboarded and "flown" on a physical simulator consisting of a control panel and monitor, a dynamic simulator, and a PDP-9 computer. The breadboard VGLIS consisted of an image dissector camera and the appropriate processing logic. Results are reported
Convex Relaxations of SE(2) and SE(3) for Visual Pose Estimation
This paper proposes a new method for rigid body pose estimation based on
spectrahedral representations of the tautological orbitopes of and
. The approach can use dense point cloud data from stereo vision or an
RGB-D sensor (such as the Microsoft Kinect), as well as visual appearance data.
The method is a convex relaxation of the classical pose estimation problem, and
is based on explicit linear matrix inequality (LMI) representations for the
convex hulls of and . Given these representations, the relaxed
pose estimation problem can be framed as a robust least squares problem with
the optimization variable constrained to these convex sets. Although this
formulation is a relaxation of the original problem, numerical experiments
indicate that it is indeed exact - i.e. its solution is a member of or
- in many interesting settings. We additionally show that this method
is guaranteed to be exact for a large class of pose estimation problems.Comment: ICRA 2014 Preprin
Automated Markerless Extraction of Walking People Using Deformable Contour Models
We develop a new automated markerless motion capture system for the analysis of walking people. We employ global evidence gathering techniques guided by biomechanical analysis to robustly extract articulated motion. This forms a basis for new deformable contour models, using local image cues to capture shape and motion at a more detailed level. We extend the greedy snake formulation to include temporal constraints and occlusion modelling, increasing the capability of this technique when dealing with cluttered and self-occluding extraction targets. This approach is evaluated on a large database of indoor and outdoor video data, demonstrating fast and autonomous motion capture for walking people
Probabilistic RGB-D Odometry based on Points, Lines and Planes Under Depth Uncertainty
This work proposes a robust visual odometry method for structured
environments that combines point features with line and plane segments,
extracted through an RGB-D camera. Noisy depth maps are processed by a
probabilistic depth fusion framework based on Mixtures of Gaussians to denoise
and derive the depth uncertainty, which is then propagated throughout the
visual odometry pipeline. Probabilistic 3D plane and line fitting solutions are
used to model the uncertainties of the feature parameters and pose is estimated
by combining the three types of primitives based on their uncertainties.
Performance evaluation on RGB-D sequences collected in this work and two public
RGB-D datasets: TUM and ICL-NUIM show the benefit of using the proposed depth
fusion framework and combining the three feature-types, particularly in scenes
with low-textured surfaces, dynamic objects and missing depth measurements.Comment: Major update: more results, depth filter released as opensource, 34
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