English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The swarm paradigm of multirobot cooperation relies on a distributed architecture, where each robot makes its own decisions based on locally available knowledge. But occasionally the swarm members may need to share information about their environment or actions through some type of ad hoc communication channel, such as a radio modem, infrared communication, or an optical connection. In all of these cases robust operation is best attained when the transmitter/receiver robot pair is (1) separated by less than some maximum distance (range constraint); and (2) not obstructed by large dense objects (line-of-sight constraint). Therefore to maintain a wireless link between two robots, it is desirable to simultaneously comply with these two spatial constraints. Given a swarm of point robots with specified initial and final configurations and a set of desired communication links consistent with the above criteria, we explore the problem of designing inputs to achieve the final configuration while preserving the desired links for the duration of the motion. Some interesting conclusions about the feasibility of the problem are offered. A potential field-based optimization algorithm is provided, along with a novel composition scheme, and its operation is demonstrated through both simulation and experimentation on a group of small robots.

Maintaining Wireless Connectivity Constraints for Robot Swarms in the Presence of Obstacles