Dolphin: a task orchestration language for autonomous vehicle networks

by   Keila Lima, et al.

We present Dolphin, an extensible programming language for autonomous vehicle networks. A Dolphin program expresses an orchestrated execution of tasks defined compositionally for multiple vehicles. Building upon the base case of elementary one-vehicle tasks, the built-in operators include support for composing tasks in several forms, for instance according to concurrent, sequential, or event-based task flow. The language is implemented as a Groovy DSL, facilitating extension and integration with external software packages, in particular robotic toolkits. The paper describes the Dolphin language, its integration with an open-source toolchain for autonomous vehicles, and results from field tests using unmanned underwater vehicles (UUVs) and unmanned aerial vehicles (UAVs).


page 5

page 6


Multi-Agent Collaboration for Building Construction

This paper details the algorithms involved and task planner for vehicle ...

Integrating Small Satellite Communication in an Autonomous Vehicle Network: A Case on Oceanography

Small satellites and autonomous vehicles have greatly evolved in the las...

Data Comets: Designing a Visualization Tool for Analyzing Autonomous Aerial Vehicle Logs with Grounded Evaluation

Autonomous unmanned aerial vehicles are complex systems of hardware, sof...

V2X Communication Between Connected and Automated Vehicles (CAVs) and Unmanned Aerial Vehicles (UAVs)

Connectivity between ground vehicles can be utilized and expanded to inc...

Adversarial Impacts on Autonomous Decentralized Lightweight Swarms

The decreased size and cost of Unmanned Aerial Vehicles (UAVs) and Unman...

Active Face Frontalization using Commodity Unmanned Aerial Vehicles

This paper describes a system by which Unmanned Aerial Vehicles (UAVs) c...

Autonomy and Unmanned Vehicles Augmented Reactive Mission-Motion Planning Architecture for Autonomous Vehicles

Advances in hardware technology have facilitated more integration of sop...