Institute of Perception, Action and Behaviour (IPAB) Director: Prof. Sethu Vijayakumar

1. Institute of Perception, Action and Behaviour (IPAB) Director: Prof. Sethu Vijayakumar

2. Anthropomorphic Robotics (Sethu Vijayakumar and Subramanian Ramamoorthy) • Biomimetic Robotics (Barbara Webb) • Graphics and Animation (Taku Komura) • Multiagent Systems (Subramanian Ramamoorthy and Michael Herrmann) • Computer Vision (Bob Fisher) • Computational Motor Control (Sethu Vijayakumar) …and there are many cross connections between these areas… IPAB Research Areas and Strengths

3. 4) Feedback 3) Sensors Sensing and Feedback: Novel ways of learning sensory-motor associations and using this to provide effective feedback for use in prosthetics In collaboration with Touch Bionics 2) Robotics 1) EMG control Anthropomorphic Robotics Machine Learning for Adaptive Control Noise • Data-driven Machine Learning methods in Sensing, Planning and Control of Robotic Systems are key for: • Scalability to large degrees of freedom • Enabling adaptation Controller Biomechanical Plant Motor Command Sensory Data Estimator Sensory Apparatus Noise

4. Dynamics Learning and Actuation Development of novel actuators. Online learning of dynamics and exploiting natural dynamics in energetically explosive tasks. In collaboration with DLR, Germany and HONDA Anthropomorphic Robotics Machine Learning for Adaptive Control Planning for Scalability New algorithms for planning under redundancy and dealing with variable stiffness and damping. Novel ways of transferring behaviour across heterogeneous plants

5. Computer Vision Sensors and Algorithms • Innovative 3D video sensor specifications and applications • 25 frames/second 3D + colour: 3D head modeling • 8 Mpixel 3D + colour: skin cancer segmentation and diagnosis • 500 frames/sec 3D + infrared: bat acoustic behaviour analysis Cosine shading Texture Mapped • Online Educational resources: • CVonline + HIPR • 700K direct accesses

6. Biomimetic Robotics Understanding sensorimotor control • Replicating auditory, visual and tactile sensing systems of insects • Algorithmic and neural models of multimodal processing in insect brains, implemented on robots • Novel and influential methodology • Recent focus on: • Navigation capabilities • Learning circuits

7. Graphics and Animation Interactive Characters • Motion planning for multiple characters • Need to avoid collisions / penetrations • New representation of movements based on spatial relationships • Simulating Interactions in cooperative / competitive environments • The characters need to learn how to collaborate or compete with human player • Game theory, reinforcement learning

8. Neurorobotics • Self organisation of • Criticality in neural networks • Behaviour in robots • General principle for exploratory control for robots with various bodies + guidance by external goals • Applied to bootstrap control in transradial hand prostheses

9. Robust Autonomy and Multiagent Systems • Autonomous decision making over time needing interaction with • complex dynamics • richly structured spaces • continual & large changes • other strategic agents and adversaries Humanoid robotics, esp. locomotion, manipulation Reactive control with layered models & multiple representations Multi-robot systems, e.g., RoboCup Strategic interaction with adversaries despite imprecise model knowledge Complex electronic markets Novel strategies and models for dealing with regime switches and extended uncertainty

10. Collaborations and Outreach Industries, Research Labs • Microsoft, HONDA (Robot Learning) • Autodesk, Namco Bandai, Blackrock Studio (Animation and Computer Games) • AIST Japan (Car design) • RIKEN • ATR (Computational Motor Contol) • Touch Bionnics (Prosthetics)