Dangerous environments

Selective attention and performance in dangerous environments.

Active Recruitment Mechanisms for Heterogeneous Robot Teams in Dangerous Environments

Using teams of autonomous, heterogeneous robots to operate in dangerous environments means increased cost-effectiveness and the ability to spread skills among team members. The high risk of loss in these domains is a challenge to team management. Teams must be able to recruit the help of other robots in the environment, while balancing searching with performing immediately useful work. This pap...

Robust Multi-Robot Coordination in Noisy and Dangerous Environments

* This work is supported by Siemens TURKEY, Tincel Kultur Vakfi TURKEY and NSF. Abstract In this paper we present the design and implementation of a complete framework for multi-robot coordination in which robots collectively execute interdependent tasks of an overall complex mission requiring diverse capabilities. Given a heterogeneous team of robots and task dependencies, proposed framework p...

Co-Evolution of Social Learning and Evolutionary Preparedness in Dangerous Environments

Danger is a fundamental aspect of the lives of most animals. Adaptive behavior therefore requires avoiding actions, objects, and environments associated with danger. Previous research has shown that humans and non-human animals can avoid such dangers through two types of behavioral adaptions, (i) genetic preparedness to avoid certain stimuli or actions, and (ii) social learning. These adaptive ...

Bumblebees (Bombus terrestris) use social information as an indicator of safety in dangerous environments.

Avoiding predation is one of the most important challenges that an animal faces. Several anti-predation behaviours can be employed, yet simply using the presence of conspecifics can be a good signal of safety in an environment with potential predation hazards. Here, we show, for the first time, that past experience of predation causes bumblebees (Bombus terrestris) to aggregate with conspecific...