LUCS Robotic Group investigates cognitive development using computational brain models and humanoid robots. By building robots that mimic the cognitive processes in humans or animals, we learn about the problems that the biological cognitive systems have to solve while simultaneously testing how our models work in practice.

Humanoid Robots

We build humanoid robots that are used to study cognitive development and human-robot interaction. Our main robotic platform is the robot Epi that exists in a number of different configurations ranging from a robotic head to a full body with two arms.

Computer Simulations of the Brain

To understand how different parts of the brain operate, we build models that can be simulated in computers or used to control robots. Our goal is to construct a large scale model of the brain that can be used to control all functions of a robot. We are particularly interested in learning, motivation and emotions and their role in cognition and have also constructed models of how the cortex develops and processes information.


We develop tools that can be used to build models of the brain. Ikaros is an infrastructure for simulation of brain models have been developed by the robotics group. The system is based on real-time streams between modules that simulate parts of the brain. Ikaros can also be used to run various cognitive experiments and for robot control.

Research Areas

Integrated Models of Memory

The goal is to design an integrated memory model that can account for a wide range of memory processes including semantic and episodic memory as well as working memory and priming. We introduce a memory model for robots that can account for many aspects of an inner world, ranging from object permanence, episodic memory, and planning to imagination and reveries. It is modeled after neurophysiological data and includes parts of the cerebral cortex together with models of arousal systems that are relevant for consciousness. The three central components are an identification network, a localization network, and a working memory network. Attention serves as the interface between the inner and the external world. It directs the flow of information from sensory organs to memory, as well as controlling top-down influences on perception. It also compares external sensations to internal top-down expectations. The model is tested in a number of computer simulations that illustrate how it can operate as a component in various cognitive tasks including perception, the A-not-B test, delayed matching to sample, episodic recall, and vicarious trial and error.

Balkenius, C., Tjøstheim, T. A., Johansson, B. & Gärdenfors, P. (2018). From focused thought to reveries: A memory system for a conscious robot. Frontiers in Robotics and AI. doi:10.3389/frobt.2018.00029 [Open Access]

Control of Pupil Dilation

We are investigating a system-level model of pupil control that includes brain regions believed to influence the size of the pupil. It includes parts of the sympathetic and parasympathetic nervous system together with the hypothalamus, amygdala, locus coeruleus, and cerebellum. Computer simulations show that the model is able to reproduce a number of important aspects of how the pupil reacts to different stimuli: (1) It reproduces the characteristic shape and latency of the light-reflex. (2) It elicits pupil dilation as a response to novel stimuli. (3) It produces pupil dilation when shown emotionally charged stimuli, and can be trained to respond to initially neutral stimuli through classical conditioning. (4) The model can learn to expect light changes for particular stimuli, such as images of the sun, and produces a “light-response” to such stimuli even when there is no change in light intensity. (5) It also reproduces the fear-inhibited light reflex effect where reactions to light increase is weaker after presentation of a conditioned stimulus that predicts punishment.

Johansson, B. and Balkenius, C. (2017). A Computational Model of Pupil Dilation. Connection Science, 5-19.

Self-Organizing Perceptual Hierarchies

We develop models of perceptual development and learning based on hierarchies of self-organizing networks.

The Control of Goal-Directed Action

How do we learn to obtain goals? We investigate different processes in the acquisition of goal-directed actions including motor control, learning inverse kinematics, reward processes and the link between attention and action.

Robot Haute Couture

We are also looking at Robot Haute Couture.


Epi Epi: A Humanoid Robot for study many different aspects of cognition.
The builder robot A special robot used within the European project Goal-Leaders. The task for the robot is to stack building blocks. Builder Robot
LUCS Robot Kit A simple but powerful robot kit for students interested in robotics.


In LUCS Robotics Group, we have built robots since 1992. Most of these are still available but most of them are no longer in use. The picture below shows some of these earlier robots.


For more information about the robotics group, contact:

Christian Balkenius. E-mail:
Birger Johansson. E-mail: