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MIARN(Modules for Intelligent Autonomous Robot Navigation) is a project of robotics perception and interaction. We provide a gui for controlling and visualizing playerstage.sf.net sensors and opencv algorithms
The below is a list of all files released for the Crossbow's MNAV100CA with SPB400. This framework may provide a complete solution for AHRS, Navigation, WiFi Comm, and Data Logging, for various robotic applications.
‘intelliworm’ is a prototype simulation of a Intelligent Species of a common earth worm,which inherits human like decision making capabilities through Neural Network intelligence representation,all developed by integrating .NET with Lisp and Yacc.
A simulation environment for 2D robots to interact and perform tasks in. Meant to be educational and demonstrate emergent behaviors. No download necessary! See demos on project website!
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Simulates and visualizes swarming algorithms with limited communication. Also provides an interface to animate particle motion by playback (with pause, fastforward, and rewind) of path information from files. Can output EPS figures and avi frames.
Plantra-Trajectory Planning is a software to rebuild surfaces from cloud points, featuring shaded 3D visualization and path planning for robotics paths. It uses Voronoi diagram, Cyrus-Beck clipping, Delaunay triangulation and B-Splines.
This project contains both tools and data for Optical Flow evaluation purposes. It offers: many ground truth optical flow sequences; a tool for generating optical flow data from real sequences; implementations of some optical flow algorithms.
CoPP is an object-oriented framework for developing algorithms for robot path planning. One of of the design goals is to make it easy to make comparisons between various path planning algorithms.
Yaobi is a fast collision detection library for general triangulated objects. It uses a hierarchical representation based on oriented bounding boxes. Yaobi compares well with other libraries when it comes to speed and memory consumption.
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General purpose agents using reinforcement learning. Combines radial basis functions, temporal difference learning, planning, uncertainty estimations, and curiosity. Intended to be an out-of-the-box solution for roboticists and game developers.
The Stanford Robotics Toolkit. An extensive, plugin-based architecture supporting the simulation and implementation of robotics algorithms. Designed for research purposes, the framework features a processing environment, a 3D GUI, and a CARMEN interface.
SLAMSim is intended to serve as an application framework for Simultaneous Localization and Mapping (SLAM) algorithms, which address the problem of simultaneously localizing a mobile robot and building a map of its operating environment.