Multi-unmanned Vehicle Research Articles

A Cooperative Decision-Making Approach Based on a Soar Cognitive Architecture for Multi-Unmanned Vehicles

A Cooperative Decision-Making Approach Based on a Soar Cognitive Architecture for Multi-Unmanned Vehicles

Enabling human-autonomy teaming with multi-unmanned vehicle control interfaces

Human-autonomy teaming is essential for future military operations, but guidance on how to design controls and displays to support joint decision-making and task completion is scarce. Transportation planning experts, drawing from their design experience, recently compiled questions that they postulated would be useful to guide human-autonomy interaction designs for other domains. To explore their generalizability, these questions were employed as a framework for describing the human-autonomy teaming interfaces developed for an implemented prototype military multi-unmanned vehicle (UV) control station. This process demonstrated that the proposed questions indeed address pertinent UV control station requirements. Their “situation driver” questions are aligned with the station’s expanded play-based adaptable automation approach, whereby a wide spectrum of control from manual to fully autonomous can be flexibly applied across UVs/mission tasks to enable shared human-autonomy workload. Their questions regarding “visualizations and control mechanisms” would have likely led to the UV station’s design that features pictorial icons to present actionable concise information in an integrated manner and intuitively support calling UV management plays. Finally, the questions addressing autonomy’s “solution generation and presentation” are correlated to the prototype’s interfaces for presenting multiple courses of action and ongoing play status. Thus, the questions inspired by military airlift planning should also be useful for human-autonomy interface design for the UV command and control domain. Suggested enhancements to the question set are provided as well as detailed recommendations on research needed to extend the human-autonomy teaming interfaces to better support bi-directional communication and directability in more complex, collaborative UV missions.

Architecture and Algorithm of Formation control of Multi-unmanned vehicles Based on Swarm intelligence

The main contents of this dissertation are the application of swarm intelligence to multi-unmanned vehicle system and the realization of cooperative control of multi-unmanned vehicle system. Firstly, this thesis introduces the research background and significance of multi-unmanned vehicle system and swarm intelligence. Secondly, we introduce the research contents of cooperative control of multi-unmanned vehicle system. Then the research status of cooperative control of multi-unmanned vehicle system in the domestic and overseas are introduced. Finally, this dissertation summarizes the mainstream types of architecture and algorithm of the multi-unmanned vehicle system.

Color-Coded Map Overlay Augmentation for Unmanned Vehicle Sensor Management

Four color-coded overlays that augment a tactical map were evaluated as candidates for multi-unmanned vehicle (UV) sensor management by a single operator. Each overlay provided six levels of temporal information to indicate how long ago each map location had been viewed by a UV. Twelve participants completed 140 trials, each trial posing a question to be answered by retrieving spatial-temporal information from static map overlays. The accuracy of the participants’ answers significantly differed as a function of overlay type. Suggestions for overlay design and future research methodology are provided.

Human-autonomy teaming interface design considerations for multi-unmanned vehicle control

ABSTRACTFuture applications are envisioned in which a single human operator manages multiple heterogeneous unmanned vehicles (UVs) by working together with an autonomy teammate that consists of several intelligent decision-aiding agents/services. This article describes recent advancements in developing a new interface paradigm that will support human-autonomy teaming for air, ground, and surface (sea craft) UVs in defence of a military base. Several concise and integrated candidate control station interfaces are described by which the operator determines the role of autonomy in UV management using an adaptable automation control scheme. An extended play calling based control approach is used to support human-autonomy communication and teaming in managing how UV assets respond to potential threats (e.g. asset allocation, routing, and execution details). The design process for the interfaces is also described including: analysis of a base defence scenario used to guide this effort, consideration of ecological interface design constructs, and generation of UV and task-related pictorial symbology.