Category Archives: Robot Applications

A robot designed to integrate socially with a group of chickens and study their behaviour

A. Gribovskiy, J. Halloy, J.L. Deneubourg, F. Mondada, Designing a socially integrated mobile robot for ethological research, Robotics and Autonomous Systems, Volume 103, 2018, Pages 42-55, DOI: 10.1016/j.robot.2018.02.003.

A robot introduced into an animal group, accepted by the animals as conspecifics, and capable of interacting with them is an efficient tool for ethological research, particularly in studies of collective and social behaviour. In this paper, we present the implementation of an autonomous mobile robot developed by the authors to study group behaviour of chicks of the domestic chicken (Gallus gallus domesticus). We discuss the design of the robot and of the experimental framework that we built to run animal–robot experiments. The robot design was experimentally validated, we demonstrated that the robot can be socially integrated into animal groups. The designed system extends the current state of the art in the field of animal–robot interaction in general and the birds study in particular by combining such advantages as (1) the robot being a part of the group, (2) the possibility of mixed multi-robot, multi-animal groups, and (3) close-loop control of robots. It opens new opportunities in the study of behaviour in domestic fowl by using mobile robots; being socially integrated into the animal group, robots can profit from the positive feedback mechanism that plays key roles in animal collective behaviour. They have potential applications in various domains, from pure scientific research to applied areas such as control and ensuring welfare of poultry.

A practical example of mobile robot long term operation

N. Hawes et al., The STRANDS Project: Long-Term Autonomy in Everyday Environments, IEEE Robotics & Automation Magazine, vol. 24, no. 3, pp. 146-156, DOI: 10.1109/MRA.2016.2636359.

Thanks to the efforts of the robotics and autonomous systems community, the myriad applications and capacities of robots are ever increasing. There is increasing demand from end users for autonomous service robots that can operate in real environments for extended periods. In the Spatiotemporal Representations and Activities for Cognitive Control in Long-Term Scenarios (STRANDS) project (http://strandsproject.eu), we are tackling this demand head-on by integrating state-of-the-art artificial intelligence and robotics research into mobile service robots and deploying these systems for long-term installations in security and care environments. Our robots have been operational for a combined duration of 104 days over four deployments, autonomously performing end-user-defined tasks and traversing 116 km in the process. In this article, we describe the approach we used to enable long-term autonomous operation in everyday environments and how our robots are able to use their long run times to improve their own performance.

An application of POMDPs to robot surveillance

S. Witwicki et al., Autonomous Surveillance Robots: A Decision-Making Framework for Networked Muiltiagent Systems, IEEE Robotics & Automation Magazine, vol. 24, no. 3, pp. 52-64, DOI: 10.1109/MRA.2017.2662222.

This article proposes an architecture for an intelligent surveillance system, where the aim is to mitigate the burden on humans in conventional surveillance systems by incorporating intelligent interfaces, computer vision, and autonomous mobile robots. Central to the intelligent surveillance system is the application of research into planning and decision making in this novel context. In this article, we describe the robot surveillance decision problem and explain how the integration of components in our system supports fully automated decision making. Several concrete scenarios deployed in real surveillance environments exemplify both the flexibility of our system to experiment with different representations and algorithms and the portability of our system into a variety of problem contexts. Moreover, these scenarios demonstrate how planning enables robots to effectively balance surveillance objectives, autonomously performing the job of human patrols and responders.