Best Poster Award na IEEE IROS Workshop – COGNITIVE VEHICLES WORKSHOP // IROS 2019

11 de November de 2019

Best Poster Award na IEEE IROS Workshop “Towards Cognitive Vehicles: perception, learning and decision making under real-world constraints. Is bio-inspiration helpful? ”

A dynamic neural model for endowing intelligent cars with the ability to learn driver routines: where to go, when to arrive and how long to stay there?“. Flora Ferreira, Weronika Wojtak, Wolfram Erlhagen, Paulo Vicente, Ankit R. Patel, Sergio Monteiro , and Estela Bicho

Towards Cognitive Vehicles: perception, learning and decision making under real-world constraints. Is bio-inspiration helpful?

The workshop will take place on November 8, 2019 in Macau, China, as part of the IROS 2019 conference. The workshop will be held at room LG-R11 (according to IROS’ room numbering) or, equivalently, Capri 1104 (according to the Venetian’s room numbering system).

Autonomous driving is only one out of many aspects of intelligence required for future transportation systems. Human-machine interaction in a cognitive vehicle is an intriguing use case that requires intelligence beyond the state of the art in machine learning, computer vision, and AI. For safe and convenient human-machine interaction, the intelligent system such as a smart vehicle needs to be able to perceive its environment and make decisions based on the received data. Current state-of-the-art approaches to both intelligent perception and decision making typically rely on machine learning with offline training of neural networks using elaborated datasets. To enable truly adaptive intelligence, as we know it from biological systems, learning that supports decision making and perception needs to happen in real time, in an online fashion. But can such adaptive perceiving, deciding, and learning systems be safe enough to actually be deployed in an intelligent vehicle?

While biological inspiration has led to some of the most successful approaches in perception and machine learning — deep neural networks, — its deployment in real-world, safety-critical settings is yet limited. We aim to explore and critically discuss what biological inspiration in perception, learning, and decision making could bring in the future for increasing intelligence of vehicles and other robotic systems.

Thus, the aim of the workshop is to discuss potential benefits and pitfalls in applying bio-inspired approaches when developing intelligent real-world systems that perceive, interact, learn, and make decisions. We will focus on the application area of intelligent, “cognitive” vehicles and will use an unconventional format: for each of three subtopics we invited 2-4 experts from different schools of thought (for example, traditional machine learning and brain-inspired learning, conventional approach to planning and decision making and cognitive architecture-based approach, event-based bio-inspired vision and conventional machine visions, etc. ). Each speaker will give a short introductory talk followed by a moderated panel discussion around each topic. Furthermore, we will invite researchers from intelligent robotics and vehicles with a focus on perception, learning and decision making to present their work in posters and short spot-light talks.

The workshop will stimulate discussion of the role of biological inspiration in the development of future AI systems in the context of real-world, safety-critical applications of robotic systems in environments shared with humans.

Topics of interest
  • Intelligent vehicles (cars, UAVs, …)
  • Human-machine interaction
  • Intelligence in the cockpit
  • Robust accountable and scalable perception with neural networks and without
  • Multi-modal perception and sensory integration
  • Attention and cognitive control in visual and tactile perception
  • Gesture recognition
  • Perception for action
  • Machine learning for vehicles
  • Fast inference and learning
  • Online learning and reliability
  • Embedded machine learning
  • Learning in complex hierarchical control systems
Cognitive Architectures
  • Cognitive architectures and machine learning / neuronal networks
  • Cognitive architectures for action selection
  • Scalable cognitive architectures
  • Learning cognitive architectures
Important Dates

Initial submission: 01.09.2019

Notification of acceptance: 10.09.2019

Camera-ready deadline: 20.09.2019

Workshop day: 08.11.2019

See our call for papers for further information on the submission process.