An experiment in integrated exploration

By Alexei Makarenko, Stefan B. Williams, Frédéric Bourgault, H. F. Durrant-Whyte. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002

370 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/8cf23231a496ee04d4383d768e3ea3d640d15b54

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Citations in the corpus

The Player/Stage Project: Tools for Multi-Robot and Distributed Sensor Systems (2003, methodology): “Several users [12, 15, 18, 29] have simulated the Pioneer 2DX pictured in Figure 1 with a position model carrying a sonar array and laser scanning rangefinder.”
Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age (2016, neutral): “us-domain avenue for active SLAM 7Other names have been used in the literature, including Simultaneous Planning Localization and Mapping (SPLAM) [191], or Autonomous, Active or Integrated Exploration [205]. 16 algorithms is the use of potential ﬁelds. Some examples are [308], which uses convolution ”
Bayesian Learning for Safe High-Speed Navigation in Unknown Environments (2015, background): “Some exploration work has balanced the objectives of information gain, navigation cost and localization quality from a utility or decision-theory point of view [16, 26].”
Trajectory Optimization using Reinforcement Learning for Map Exploration (2008, background): “There is an abundance of related work using information gain for choosing actions, among which the most closely related comes from ( Makarenko et al. 2002; Stachniss 2006; Feder et al. 1999; Sim 2006).”
Vision-based autonomous mapping and exploration using a quadrotor MAV (2012, neutral): “This essentially turns our mapping algorithm into active mapping [18] where waypoints are selected autonomously based on the exploration strategy.”
Information Gain-based Exploration Using Rao-Blackwellized Particle Filters (2005, background): “As can be seen from this experiment, as soon as the robot gets too uncertain about its pose, it performs place re-visiting actions or chooses exploration actions which also reduce its pose uncertainty due to the information gathered along the path.”
A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontiers (2022, methodology): “In fact, the latter approximates the map’s entropy, which is strongly related to the number of known cells in an OG map [28].”
SARSOP: Efficient Point-Based POMDP Planning by Approximating Optimally Reachable Belief Spaces (2008, neutral): “This is sometimes called integrated exploration [8].”