Robot Path Planning in a Social Context

Publication Type:
Conference Proceeding
Proceedings of The International Conference on Robotics, Automation and Mechatronics (RAM), 2010, pp. 206 - 211
Issue Date:
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2010000657.pdf1.56 MB
Adobe PDF
Human robot interaction has attracted significant attention over the last couple of years. An important aspect of such robotic systems is to share the working space with humans and carry out the tasks in a socially acceptable way. In this paper, we address the problem of fusing socially acceptable behaviours into robot path planning. By observing an environment for a while, the robot learns human motion patterns based on sampled Hidden Markov Models and utilises them in a Probabilistic Roadmap based path planning algorithm. This will minimise the social distractions, such as going through someone else's working space (due to the shortest path), by planning the path through minimal distractions, leading to human-like behaviours. The algorithm is implemented in Orca/C++ with appealing results in real world experiments.
Please use this identifier to cite or link to this item: