Projects at AASS
The Center for Applied Autonomous Sensor Systems conducts a number of research projects, often in close collaboration with industry. Below is the complete list of projects.
The Center also currently runs a larger cross-lab project called Semantic Robots which is funded the Swedish Knowledge Foundation (KKS). More about the Semantic Robots project can be found here.
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GeRT - Generalizing Robot Manipulation Tasks
In order to work naturally in human environments such as offices and homes, robots of the future will need to be much more flexible and robust in the face of...
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GiraffPlus
In this project we propose to develop and thoroughly evaluate a complete system, called the GiraffPlus. The system collects daily behaviour and physilogical...
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Ground-level power supply for electrical vehicles
The project is part of a big project finance by Energimyndigheten about electrified highways. The task is to develop the interface between the vehicle and th...
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Human-aware task planning for mobile robots
One of the major challenges in robotics is to have mobile robots operate in environments that are inhabited by humans, such as homes, shops, warehouses, and...
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Human-in-the-loop: Modeling and Simulation
Agent-based simulation forms an innovative simulation paradigm with great potential. Such a model is based on the metaphor of a multi-agent system which can...
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ILIAD: Intra-Logistics with Integrated Automatic Deployment for safe and scalable fleets in shared spaces
Today, intralogistic services have to respond quickly to changing market needs, unforeseeable trends and shorter product life cycles. These drivers pose new...
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iQMobility
The iQMobility project deals with developing fleets of autonomous buses. The project is led by Scania and also involves KTH and the company INIT. Our role in...
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Learning Agents for Supporting Modeling
The process of identifying and modelling the appropriate agent behavior is a cumbersome task -- no matter whether it is for agent-based software or agent-bas...
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Long Term Symbol Anchoring for Dynamic and Realistic Environments
One of the most important challenges that intelligent systems are now facing is to acquire the ability to operate in realistic environments and interact with...
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Machine Learning to enhance AI Planning for Intelligent Transport Systems
AI planning and scheduling methods are fundamental in industrial transport applications, automating key stages in the overall process of assigning tasks and...