The design and control of a robot are very tightly coupled. The way we design a robot determines the way it can be controlled, and vice versa. Machine learning can be applied not only to optimize the robot motion controllers, but also to evolve robot designs with a particular design objective in mind.

Jumping robot with active and passive compliance

Jumping robot with active and passive compliance. Energy efficiency is achieved by using a bungee cord for energy storage during continuous hopping. We investigate how active and passive compliance can help to absorb the shock of landing impact and protect the robot.

Kinematic-free Position Control of a Robot Arm

Kinematic-free Position Control of a Robot Arm. A novel concept for position control of a robot arm based on encoderless robot controller that does not rely on any joint angle sensing.

Haptic Exploration of Unknown Surfaces with Discontinuities

Haptic Exploration of Unknown Surfaces with Discontinuities

Robot WALK-MAN at DARPA Robotics Challenge

The WALK-MAN robot is getting ready for the DARPA Robotics Challenge 2015

Testing the impedance controller and puppeteering contol mode on Robot DE NIRO

Testing the impedance controller and puppeteering contol mode on Robot DE NIRO

Autonomous Robot Valve Turning

Autonomous Robot Valve Turning. The robot learns how to react to different disturbances during the task execution in response to the changes of the uncertainty in the valve position.

Publications

  1. Fabian Falck, Sagar Doshi, Marion Tormento, Gor Nersisyan, Nico Smuts, John Lingi, Kim Rants, Roni Permana Saputra, Ke Wang, Petar Kormushev, "Robot DE NIRO: A Human-Centered, Autonomous, Mobile Research Platform for Cognitively-Enhanced Manipulation", In Frontiers in Robotics and AI, 2020.
  2. Fabian Falck, Kawin Larppichet, Petar Kormushev, "DE VITO: A Dual-arm, High Degree-of-freedom, Lightweight, Inexpensive, Passive Upper-limb Exoskeleton for Robot Teleoperation", In Proc. 20th International Conference Towards Autonomous Robotic Systems (TAROS 2019), London, UK, 2019. (Best Paper Award)
  3. Nemanja Rakicevic, Petar Kormushev, "Active Learning via Informed Search in Movement Parameter Space for Efficient Robot Task Learning and Transfer", In Autonomous Robots, Springer, 2019.
  4. Fabian Falck, Sagar Doshi, Nico Smuts, John Lingi, Kim Rants, Petar Kormushev, "Human-centered manipulation and navigation with Robot DE NIRO", In IROS 2018 Workshop: Towards Robots that Exhibit Manipulation Intelligence, IEEE/RSJ Intl Conf. on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018.
  5. Roni Permana Saputra, Petar Kormushev, "ResQbot: A Mobile Rescue Robot with Immersive Teleperception for Casualty Extraction", In Proc. 19th International Conference Towards Autonomous Robotic Systems (TAROS 2018), Bristol, UK, 2018.
  6. Roni Permana Saputra, Petar Kormushev, "ResQbot: A Mobile Rescue Robot for Casualty Extraction", In Proc. 2018 ACM/IEEE International Conference on Human-Robot Interaction (HRI 2018), Chicago, USA, pp. 239-240, 2018.