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Found 36 papers, 11 papers with code
Learning Symbolic Task Representation from a Human-Led Demonstration: A Memory to Store, Retrieve, Consolidate, and Forget Experiences
We present a symbolic learning framework inspired by cognitive-like memory functionalities (i. e., storing, retrieving, consolidating and forgetting) to generate task representations to support high-level task planning and knowledge bootstrapping.
OWLOOP: Interfaces for Mapping OWL Axioms into OOP Hierarchies
The issues of mapping OWL axioms hierarchies and OOP objects hierarchies are due to OWL-based reasoning algorithms, which might change an OWL hierarchy at runtime; instead, OOP hierarchies are usually defined as static structures.
Safe motion planning with environment uncertainty
Moreover, possible occlusions and dynamic objects in the environment render imperfect landmark estimation.
A Framework for Neurosymbolic Robot Action Planning using Large Language Models
Symbolic task planning is a widely used approach to enforce robot autonomy due to its ease of understanding and deployment.
Computational Tradeoff in Minimum Obstacle Displacement Planning for Robot Navigation
In this paper, we look into the minimum obstacle displacement (MOD) planning problem from a mobile robot motion planning perspective.
Robots with Different Embodiments Can Express and Influence Carefulness in Object Manipulation
Humans have an extraordinary ability to communicate and read the properties of objects by simply watching them being carried by someone else.
Minimum Displacement Motion Planning for Movable Obstacles
This paper presents a minimum displacement motion planning problem wherein obstacles are displaced by a minimum amount to find a feasible path.
Synthesis and Execution of Communicative Robotic Movements with Generative Adversarial Networks
Object manipulation is a natural activity we perform every day.
OWLOOP: A Modular API to Describe OWL Axioms in OOP Objects Hierarchies
OWLOOP is an Application Programming Interface (API) for using the Ontology Web Language (OWL) by the means of Object-Oriented Programming (OOP).
Dynamic Human-Robot Role Allocation based on Human Ergonomics Risk Prediction and Robot Actions Adaptation
Despite cobots have high potential in bringing several benefits in the manufacturing and logistic processes, but their rapid (re-)deployment in changing environments is still limited.
Exact and Bounded Collision Probability for Motion Planning under Gaussian Uncertainty
Computing collision-free trajectories is of prime importance for safe navigation.
Task Allocation for Multi-Robot Task and Motion Planning: a case for Object Picking in Cluttered Workspaces
We present an AND/OR graph-based, integrated multi-robot task and motion planning approach which (i) performs task allocation coordinating the activity of a given number of robots, and (ii) is capable of handling tasks which involve an a priori unknown number of object re-arrangements, such as those involved in retrieving objects from cluttered workspaces.
From Movement Kinematics to Object Properties: Online Recognition of Human Carefulness
This study is a step towards endowing a humanoid robot with this last capability.
Property-Aware Robot Object Manipulation: a Generative Approach
When transporting an object, we unconsciously adapt our movement to its properties, for instance by slowing down when the item is fragile.
Human Activity Recognition Models in Ontology Networks
Arianna+ schedules procedures on the basis of events by employing logic-based reasoning, i. e., by checking the classification of certain statements in the ontologies.
MPTP: Motion-Planning-aware Task Planning for Navigation in Belief Space
A reasonable comparison with a work that is closest to our approach is also provided.
A Task-Motion Planning Framework Using Iteratively Deepened AND/OR Graph Networks
While retrieving a target object from clutter, the number of object re-arrangements required to grasp the target is not known ahead of time.
Careful with That! Observation of Human Movements to Estimate Objects Properties
Our final goal is to enable a robot to autonomously infer the degree of care required in object handling and to discriminate whether the item is light or heavy, just by observing a human manipulation.
An Integrated Localisation, Motion Planning and Obstacle Avoidance Algorithm in Belief Space
We present a novel approach (1) to incorporate these uncertainties for robot state estimation and (2) to compute the probability of collision pertaining to the estimated robot configurations.
Manipulation of Articulated Objects using Dual-arm Robots via Answer Set Programming
We validate the overall framework in the extended scenario, thereby confirming the applicability of ASP also in more realistic Robotics settings, and showing the usefulness of macro actions for the robot-based manipulation of articulated objects.
Towards Multi-Robot Task-Motion Planning for Navigation in Belief Space
Autonomous robots operating in large knowledgeintensive domains require planning in the discrete (task) space and the continuous (motion) space.
A Hierarchical Architecture for Human-Robot Cooperation Processes
In this paper we propose FlexHRC+, a hierarchical human-robot cooperation architecture designed to provide collaborative robots with an extended degree of autonomy when supporting human operators in high-variability shop-floor tasks.
Deployment and Evaluation of a Flexible Human-Robot Collaboration Model Based on AND/OR Graphs in a Manufacturing Environment
The Industry 4. 0 paradigm promises shorter development times, increased ergonomy, higher flexibility, and resource efficiency in manufacturing environments.
Multi-sensory Integration in a Quantum-Like Robot Perception Model
Given a 3-dimensional case study, we highlight how this model provides a compact and elegant representation, embodying features that are extremely useful for modeling uncertainty and decision.
Task-Motion Planning for Navigation in Belief Space
Furthermore, our framework is intended for motion planning under motion and sensing uncertainty, which is formally known as belief space planning.
Task-assisted Motion Planning in Partially Observable Domains
We present an integrated Task-Motion Planning framework for robot navigation in belief space.
Online Human Gesture Recognition using Recurrent Neural Networks and Wearable Sensors
Gestures are a natural communication modality for humans.
Robotics
Arianna+: Scalable Human Activity Recognition by Reasoning with a Network of Ontologies
For a system to perform human activity recognition in a real-world environment, multiple requirements exist, such as scalability, robustness, ability to deal with uncertainty (e. g., missing sensor data), to operate with multi-occupants and to take into account their privacy and security.
A 2D laser rangefinder scans dataset of standard EUR pallets
The data have been manually labelled and are provided in different formats.
Detection, localisation and tracking of pallets using machine learning techniques and 2D range data
The problem of autonomous transportation in industrial scenarios is receiving a renewed interest due to the way it can revolutionise internal logistics, especially in unstructured environments.
A framework for Culture-aware Robots based on Fuzzy Logic
Cultural adaptation, i. e., the matching of a robot's behaviours to the cultural norms and preferences of its user, is a well known key requirement for the success of any assistive application.
Towards a new paradigm for assistive technology at home: research challenges, design issues and performance assessment
Providing elderly and people with special needs, including those suffering from physical disabilities and chronic diseases, with the possibility of retaining their independence at best is one of the most important challenges our society is expected to face.
Scene learning, recognition and similarity detection in a fuzzy ontology via human examples
This paper introduces a Fuzzy Logic framework for scene learning, recognition and similarity detection, where scenes are taught via human examples.
Detection of bimanual gestures everywhere: why it matters, what we need and what is missing
Bimanual gestures are of the utmost importance for the study of motor coordination in humans and in everyday activities.
A ROS multi-ontology references services: OWL reasoners and application prototyping issues
This paper introduces a ROS Multi Ontology References (ARMOR) service, a general-purpose and scalable interface between robot architectures and OWL reasoners.
Visuospatial Skill Learning for Robots
A novel skill learning approach is proposed that allows a robot to acquire human-like visuospatial skills for object manipulation tasks.
