EASE Research Areas
The research activities of the CRC EASE are structured into three main Research Areas (H, P and R). Each Research Area consists of several subprojects. On the following page you find an overview of the subprojects, their research focus, and leaders (Principal Investigators).
Further subprojects include the Project Management and Central Services (Z) for the administration and coordination of the CRC as a whole, the Integrated Research Training Group (MGK), the Information Infrastructure (INF) for the storage, management, and maintenance of the data generated by EASE, and the Laboratory Infrastructure Support (F) for the establishment of the EASE central robotics lab.
The goal of Research Area H is to understand why and how humans can perform vague instructions for everyday activities efficiently and respond quickly and flexibly to new situations. It investigates hypotheses about the form and role of Pragmatic Everyday Activity Manifolds (PEAMs) in competent human everyday manipulation tasks. Its aim is to design computational mechanisms that achieve such efficiency and are as adaptive as human activities.
- H01: Acquiring activity models by situating people in virtual environments
(Akquisition von menschlichen Aktivitätsmodellen in virtuellen Umgebungen)
Performance of controlled experiments with humans performing manipulation tasks in specially designed virtual environments to investigate everyday activity strategies in unfamiliar or unexpected situations.
Subproject Leaders (PI): Prof. Dr. Kerstin Schill, Prof. Dr. Gabriel Zachmann, Dr. Christoph Zetzsche.
- H02: Mining and explicating instructions for everyday activities
(Akquisition und Explikation von Instruktionen für Alltagsaktivitäten)
Investigation of methods for obtaining knowledge about everyday activities through reading instructions from the web. Disambiguation and completion of the instructions using simulation and Games with a Purpose.
Subproject Leaders (PI): Prof. Dr. Rainer Malaka, Prof. Dr. John Bateman.
- H03: Natural activity statistics
(Statistische Eigenschaften von Alltagsaktivitäten)
Collection, Annotation, Analysis, and Interpretation of complex human everyday activities by a combination of statistically driven bottom-up and guided top-down methods in order to detect PEAMs, on which generative models of human activities will be learned.
Subproject Leaders (PI): Prof. Dr. Kerstin Schill, Prof. Dr. Tanja Schultz, Prof. Dr. Manfred Herrmann.
The goal of Research Area P is to understand the representation and reasoning foundations of information processing methods that enable robotic agents to master everyday activities. The knowledge about everyday activity from Research Area H needs to be represented such that it is useful to artificial systems. Research Area P investigates the representational foundations, reasoning techniques and formalizations of Narrative-enabled Episodic Memories (NEEMs), and common knowledge and plans for mastering everyday activities. Its aim is to design representation and reasoning mechanisms that capture the intuitions behind human acitivies. It uses information from Research Area H while at the same time providing feedback to Research Area H.
- P01: Embodied semantics for the language of action and change
(Aktionsbasierte Semantik für die Sprache von Handlung und Wirkung)
Investigation of simulated-based semantics for action steps (based on the respective action verb) that constitute the atomic steps of narratives and creation of logical formalizations of compound narratives.
Subproject Leaders (PI): Prof. Dr. John Bateman, Prof. Dr. Rainer Malaka.
- P02: Rightsizing ontologies
Investigation of the fundamental trade-off between expressiveness and tractabiity in ontological reasoning by identifying PEAMs for reasoning that have just the right expressiveness.
Subproject Leaders (PI): Prof. Dr. Carsten Lutz, Prof. Dr. John Bateman.
- P03: Spatial reasoning in everyday activity
(Räumliches Schließen in Alltagsaktivitäten)
Performance of an in-depth investigation of the spatio-temporal aspects of reasoning about everyday activity in particular. Investigation of PEAMs in this domain.
Subproject Leader (PI): Dr. habil. Holger Schultheis.
- P04: Formalizations and properties of plans
(Formalisierung und Eigenschaften von Plänen)
Investigation of formalizations and axiomatizations of the plans used by the robot to perform everyday activities. Development of methods for the verification of safety constrains of the generated robot plans such that heuristic planning and learning methods can be used without compromising safety.
Subproject Leaders (PI): Prof. Dr. Rolf Drechsler, Dr. Daniel Große.
The goal of Research Area R is to investigate a control framwework including perception, learning, and reasoning mechanisms that enable robotic agents to master human-scale everyday manipulation tasks. It investigates the information processing infrastructure necessary for robotic agents to take vague task descriptions and use information about the task, situational context, and object context to perform the task appropriately. This infrastructure will improve with experience (NEEMs) and by exploiting the routine and mundane character of everyday activity tasks by making use of the PEAMs investigated in the Research Areas H and P. Simultaneously, the findings from Research Area R are fed back to both Research Area hH and P.
- R01: NEEM-based embodied knowledge system
(NEEM-basiertes integriertes Wissenssystem)
Design and realization of the subcomponent of the information processing and control system that acquires and amanages NEEMs, and abstraction of the information contained in NEEMs into generalized knowledge.
Subproject Leaders (PI): Prof. Dr. h.c. Michael Beetz PhD, Prof. Dr. Gordon Cheng.
- R02: Multi-cue perception based on background knowledge
(Hintergrundwissen für Multi-Komponenten-Perzeption)
Investigation of the efficient and robust accomplishment of selected challenging perception problems in the context of everyday activity that require common knowledge and the exploitation of PEAMs.
Subproject Leader (PI): Prof. Dr. Udo Frese.
- R03: Embodied simulation-enabled reasoning
(Integriertes simulations-basiertes Schließen)
Investigation of embodied reasoning methods that use simulation-based prediction. This subproject also aims to develop faster-than-realtime simulators.
Subproject Leaders (PI): Prof. Dr. Gabriel Zachmann, Prof. Dr. h.c. Michael Beetz PhD.
- R04: Specializing and optimizing generic robot plans
(Spezialisierung und Optimierung generischer Roboter-Pläne)
Realization of control systems for robots for performing the household chores in the main scenario, including preparing simple meals, setting the table, cleaning up, shopping, and storing purchase items. Scientifically the subproject investigates how plans can be optimized through specialization by exploiting the PEAMs of the respective everyday activity.
Subproject Leaders (PI): Prof. Dr. h.c. Michael Beetz PhD, Prof. Dr. Alin Albu-Schäffer.
- R05: Episodic memory for everyday manual activities
(Episodische Gedächtnisse für manuelle Alltagsaktivitäten)
Investigation of how collections of NEEMs of everyday manual actions can be obtained for robots and how they can be used to bridge between semantic, procedural, and perceptual memories in order to support competent and dexterous manipulation in everyday contexts.
Subproject Leaders (PI): Prof. Dr. Helge Ritter, Prof. Dr. h.c. Michael Beetz PhD.
Pictures taken at the Automatica 2018 in Munich: Human demonstrations in a virtual environment. Visitors could put on VR glasses and move around in a virtual kitchen. 3D Modelling is used in several Research Areas.
Photo Credits: Wibke Borngesser (TUM).