A field-tested robotic harvesting system for iceberg lettuce
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The ability of building robust semantic space representations of environments is crucial for the development of truly autonomous robots. This task, inherently connected with cognition, is traditionally achieved by training the robot with a supervised learn ...
For many real-life applications such as monitoring, mapping, search-and-rescue or ad-hoc communication networks, fleets of flying robots are expected to out-perform existing solutions. Robots can join forces to cover larger areas in less time, act as effic ...
The ability of building robust semantic space representations of environments is crucial for the development of truly autonomous robots. This task, inherently connected with cognition, is traditionally achieved by training the robot with a supervised learn ...
The ability of building robust semantic space representations of environments is crucial for the development of truly autonomous robots. This task, inherently connected with cognition, is traditionally achieved by training the robot with a supervised learn ...
This paper extends prior work using Compositional Pattern Producing Networks (CPPNs) as a generative encoding for the purpose of simultaneously evolving robot morphology and control. A method is presented for translating CPPNs into complete robots includin ...
Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using online learning techniques which allow robots to generate their own controllers online in an automated fash- ion. In multi- ...
Automatic recognition of gestures using computer vision is important for many real-world applications such as sign language recognition and human-robot interaction (HRI). Our goal is a real-time hand gesture-based HRI interface for mobile robots. We use a ...
The work of this thesis centers around the research subject of distributed robotic search. Within the field of distributed robotic systems, a task of particular interest is attempting to locate one or more targets in a possibly unknown environment. While n ...
We apply an adapted version of Particle Swarm Optimization to distributed unsupervised robotic learning in groups of robots with only local information. The performance of the learning technique for a simple task is compared across robot groups of various ...
