SUAVE: An Exemplar for Self-Adaptive Underwater Vehicles

Once deployed in the real world, autonomous underwater vehicles (AUVs) are out of reach for human supervision yet need to take decisions to adapt to unstable and unpredictable environments. To facilitate research on self-adaptive AUVs, this paper presents SUAVE, an exemplar for two-layered system-level adaptation of AUVs, which clearly...

MROS: A framework for robot self-adaptation

Self-adaptation can be used in robotics to increase system robust- ness and reliability. This work describes the Metacontrol method for self-adaptation in robotics. Particularly, it details how the MROS (Metacontrol for ROS Systems) framework implements and pack- ages Metacontrol, and it demonstrate how MROS can be applied in a navigation...

Active Inference and Behavior Trees for Reactive Action Planning and Execution in Robotics

In this article, we propose a hybrid combination of active inference and behavior trees (BTs) for reactive action planning and execution in dynamic environments, showing how robotic tasks can be formulated as a free-energy minimization problem. The proposed approach allows handling partially observable initial states and improves the...

A Formal Model of Metacontrol in Maude

Nowadays smart applications appear in domains spanning from commodity household applications to advanced underwater robotics. These smart applications require adaptation to dynamic environments, changing requirements and internal system errors Metacontrol takes a systems of systems view on autonomous control systems and self-adaptation, by...

Towards Stochastic Fault-Tolerant Control Using Precision Learning and Active Inference

This work presents a fault-tolerant control scheme for sensory faults in robotic manipulators based on active inference. In the majority of existing schemes a binary decision of whether a sensor is healthy (functional) or faulty is made based on measured data. The decision boundary is called a threshold and it is usually deterministic....

Fault-tolerant Control of Robot Manipulators with Sensory Faults using Unbiased Active Inference

This work presents a novel fault-tolerant control scheme based on active inference. Specifically, a new formulation of active inference which, unlike previous solutions, provides unbiased state estimation and simplifies the definition of probabilistically robust thresholds for fault-tolerant control of robotic systems using the free-energy. The...

A Modeling Tool for Reconfigurable Skills in ROS

Known attempts to build autonomous robots rely on complex control architectures, often implemented with the Robot Operating System platform (ROS). The implementation of adaptable architectures is very often ad hoc, quickly gets cumbersome and expensive. Reusable solutions that support complex, runtime reasoning for robot adaptation have been...

Functional self-awareness and metacontrol for underwater robot autonomy

Autonomous systems are expected to maintain a dependable operation without human intervention. They are intended to fulfill the mission for which they were deployed, properly handling the disturbances that may affect them. Underwater robots, such as the UX-1 mine explorer developed in the UNEXMIN project, are paradigmatic examples of this...

A Novel Adaptive Controller for Robot Manipulators Based on Active Inference

More adaptive controllers for robot manipulators are needed, which can deal with large model uncertainties. This letter presents a novel active inference controller (AIC) as an adaptive control scheme for industrial robots. This scheme is easily scalable to high degrees-of-freedom, and it maintains high performance even in the presence of...

Active inference for fault tolerant control of robot manipulators with sensory faults

We present a fault tolerant control scheme for robot manipulators based on active inference. The proposed solution makes use of the sensory prediction errors in the free-energy to simplify the residuals and thresholds generation for fault detection and isolation and does not require additional controllers for fault recovery. Results...

Meta-control and Self-Awareness for the UX-1 Autonomous Underwater Robot

Autonomous underwater robots, such as the UX-1 developed in the UNEXMIN project, need to maintain reliable autonomous operation in hazardous and unknown environments. Because of the lack of any kind of real-time communications with a human operated command and control station, the control architecture needs to be enhanced with mission-level...

Integrating different levels of automation: Lessons from winning the Amazon Robotics Challenge 2016

This article describes Team Delft's robot winning the Amazon Robotics Challenge 2016. The competition involves automating pick and place operations in semi-structured environments, specifically the shelves in an Amazon warehouse.<br/>Team Delft's entry demonstrated that current robot technology can already address most of the challenges in...

A self-adaptation framework based on functional knowledge for augmented autonomy in robots

Robot control software endows robots with advanced capabilities for autonomous operation, such as navigation, object recognition or manipulation, in unstructured and dynamic environments. However, there is a steady need for more robust operation, where robots should perform complex tasks by reliably exploiting these novel capabilities. Mission...

Model-based systems engineering to design collaborative robotics applications

Novel robot technologies are becoming available to automate more complex tasks, more flexibly, and collaborating with humans. Methods and tools are needed in the automation and robotics industry to develop and integrate this new breed of robotic systems. In this paper, the ISE&amp;PPOOA methodology for Model-Based Systems Engineering is...