Qualitative relational mapping and navigation for planetary rovers

  title={Qualitative relational mapping and navigation for planetary rovers},
  author={Mark McClelland and Mark E. Campbell and Tara A. Estlin},
  journal={Robotics Auton. Syst.},
This paper presents a novel method for qualitative mapping of large scale spaces which decouples the mapping problem from that of position estimation. The proposed framework makes use of a graphical representation of the world in order to build a map consisting of qualitative constraints on the geometric relationships between landmark triplets. This process allows a mobile robot to extract information about landmark positions using a set of minimal sensors in the absence of GPS. A novel… 
Q-Link: A general planning architecture for navigation with qualitative relational information
Qualitative linking (Q-Link), a general three level planning architecture for use with any type of QRM, is introduced, which generates high level plans over ‘links’ in a QRM and uses local planners to execute trajectories to enable a robot to navigate from a start to a goal.
Guided navigation from multiple viewpoints using qualitative spatial reasoning
Two qualitative-probabilistic algorithms for guided navigation using a particle filter and qualitative spatial relations are presented, which assumes relations from the qualitative spatial reasoning formalism called StarVars, whose inference method is used to build a model of the domain.
The Heuristic of Directional Qualitative Semantic: A New Heuristic for Making Decisions about Spinning with Qualitative Reasoning
A new heuristic, the Heuristic of Directional Qualitative Semantic (HDQS), is presented, which allows for selecting a spinning action to establish a directional relation between an agent and an object.
Probabilistic qualitative mapping for robots
  • J. Padgett, M. Campbell
  • Computer Science
    2016 IEEE International Conference on Robotics and Automation (ICRA)
  • 2016
Probabilistic distributions over qualitative states are derived and an algorithm to update the map recursively is developed to enable robots to robustly map environments using noisy sensor measurements.
Probabilistic qualitative mapping for robots
Probabilistic distributions over qualitative states are derived and an algorithm to update the map recursively is developed to enable robots to robustly map environments using noisy sensor measurements.


Qualitative Relational Mapping for Mobile Robots with Minimal Sensing
A novel measurement method based on camera imagery is presented that extends previous work from the field of qualitative spatial reasoning and constructs a graph-based map that encodes the relative location of landmarks in the environment.
A Qualitative Approach to Localization and Navigation Based on Visibility Information
A model for navigation of an autonomous agent in which localization, path planning, and locomotion is performed in a qualitative manner instead of relying on exact coordinates is described.
Navigation and Mapping in Large Scale Space
It is proposed that robust navigation and mapping systems for large- scale space can be developed by adhering to a natural, four-level semantic hierarchy of descriptions for representation, planning, and execution of plans in large-scale space.
Globally Consistent Range Scan Alignment for Environment Mapping
The problem of consistent registration of multiple frames of measurements (range scans), together with therelated issues of representation and manipulation of spatialuncertainties are studied, to maintain all the local frames of data as well as the relative spatial relationships between localframes.
FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance
A probabilistic approach to the problem of recognizing places based on their appearance that can determine that a new observation comes from a previously unseen place, and so augment its map, and is particularly suitable for online loop closure detection in mobile robotics.
Robocentric map joining: Improving the consistency of EKF-SLAM
A mapping algorithm, Robocentric Map Joining, which improves consistency of the EKFSLAM algorithm by limiting the level of uncertainty in the continuous evolution of the stochastic map by using a robot centered representation of each local map.
Incremental vision-based topological SLAM
This paper proposes a vision-based framework that considers this data association problem from a loop-closure detection perspective in order to correctly assign each measurement to its location.
Vast-scale Outdoor Navigation Using Adaptive Relative Bundle Adjustment
A new relative bundle adjustment is derived which, instead of optimizing in a single Euclidean space, works in a metric space defined by a manifold, and it is shown experimentally that it is possible to solve for the full maximum-likelihood solution incrementally in constant time, even at loop closure.
Qualitative Spatial Reasoning for Topological Map Learning
A topological mapping framework is developed that achieves robustness against ambiguity in the available information by tracking all possible graph hypotheses simultaneously and exploiting spatial reasoning to reduce the space of possible hypotheses.
The visual homing problem : An example of robotics / biology cross fertilization
In this paper, we describe how a mobile robot under simple visual control can retrieve a particular goal location in an open environment. Our model neither needs a precise map nor to learn all the