A mobile robot employing insect strategies for navigation

By D. Lambrinos, R. Möller, T. Labhart, Rolf Pfeifer, Rüdiger Wehner. Robotics Auton. Syst., 2000

563 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Genetics, Insect Science

View Paper: https://www.semanticscholar.org/paper/ca8efde003d0a05c79a9569527686983297b5303

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In Cellular and Molecular Neuroscience

Rolf Pfeifer

In Genetics

Citations in the corpus

Visual Homing From Scale With an Uncalibrated Omnidirectional Camera (2013, methodology): “Second, the outputting homing vector of the ALV algorithm highly depends on the estimation of the global orientation.”
Bee-inspired foraging in an embodied swarm (2011, unknown): “During exploration and exploitation, the foraging robots are able to compute their present location from their past trajectory continuously and, as a consequence, can return to their starting point by choosing the direct route rather than retracing their outbound trajectory [2, 6].”
Stigmergic landmark foraging (2009, background): “Bees are able to compute their present location from their past trajectory continuously and, as a consequence, can return to their starting point by choosing the direct route rather than retracing their outbound trajectory [15, 21].”
Swarm Intelligence in Optimization (2008, methodology): “For example, the path finding and orientation skills of the desert ant Cataglyphis were used as an archetype for building a robot orientation unit [98].”
What can we learn from studies of insect navigation (2012, methodology): “The classic Snapshot model (Cartwright & Collett 1983) and derivatives (Franz et al. 1998; Lambrinos et al. 2000; Zeil et al. 2003; Vardy & Möller 2005; Möller & Vardy 2006) treat a single view as an attractor, which can be approached from any direction.”
Two foraging algorithms for robot swarms using only local communication (2010, background): “Multiple researchers have studied foraging and other pheromone-mediated coordination, and have reduced this behavior to algorithms [2], [3], [4], [5].”
Faux frogs : multimodal signalling and the value of robotics in animal behaviour (2008, background): “Examples of these include studies of navigation (Lambrinos et al. 2000) and chemical trail following (Kuwana & Shimoyama 1998; Grasso et al. 2000).”
Embodied Artificial Intelligence: Trends and Challenges (2003, background): “Jointly, they built a series of robots, the Sahabot-Series that mimic long- and short-term navigation behavior of the desert ant Cataglyphis (e.g. Lambrinos et al., 2000).”
Catchment areas of panoramic snapshots in outdoor scenes. (2003, methodology): “So far, the most parsimonious model for view-based homing is probably the average landmark vector scheme, proposed by Lambrinos et al.10 and Möller11.”
How the body shapes the way we think - a new view on intelligence (2006, background): “Lambrinos, together with his colleague Ralf Möller, developed another navigation model, the so-called average landmark vector model (Lambrinos et al., 2000), which is even simpler than the snapshot model.”