Mobile Manipulators

The main objective of Manfred Mobile Manipulator is the development of new capabilities to operate into the environment. The development of a new sensor-based planning and control architecture will allow the integration of sensor information coming from a laser scan, vision and a force/torque sensor. To reach this aim efficiently three complementary goals are required:
1. The functional architecture integrates perception, control, local and global planning in order to the mobile manipulator can cope with a wide spectrum of typical tasks required for a service robot operating in indoor environments (displacement in not cluttered areas, displacement in cluttered areas, door opening and collaboration with humans in the transport of a simple object). The architecture will be based on external sensor feedback for interaction control and sensor based local planning to achieve a proper combination of reactivity to environment and smoothness in interaction control with objects.
2. The interaction control system is based on a sensorial feedback of an impedance control. By introducing the positional error between the arm end effector and the object as sensor feedback in the impedance control loop, the tolerance to position uncertainty of the mobile manipulator will be improved considerably. The force control strategy will be based on an impedance control due to the object to manipulate are not exactly the same and the task will be sporadically done.
3. The perception system is based on a laser scanner (2D and 3D) and vision (one in hand and a frontarl camera) used to solve the displacements and approximation problems, and a vision system will be used to estimate the positional error during the interaction task.

Manfred_v2_1

Entries:
Automatic Demonstration and Feature Selection for Robot Learning
IEEE International Conference on Humanoid Robots, 2015, Seoul, South Korea
S. Morante Juan G. Victores
Action Effect Generalization, Recognition and Execution through Continuous Goal-Directed Actions
IEEE International Conference on Robotics and Automation (ICRA 2014), 2014, Hong Kong, China
S. Morante Juan G. Victores A. Jardon
On Using Guided Motor Primitives to Execute Continuous Goal-Directed Actions
IEEE international symposium on robot and human interactive communication (RO-MAN 2014), 2014, Edinburgh, Scotland
S. Morante Juan G. Victores A. Jardon
Towards Robot Imagination Through Object Feature Inference
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013)., 2013, Tokyo, Japan
Juan G. Victores S. Morante A. Jardon
On Using Humanoid Robot Imagination to Perform the Shortened Token Test
IEEE RAS International Conference on Humanoid Robots (Humanoids 2014), 2014, Madrid, Spain
Juan G. Victores S. Morante A. Jardon
Semantic Action Parameter Inference through Machine Learning Methods
RoboCity2030 12th Workshop: Robótica Cognitiva, 2013, Madrid, Spain
Juan G. Victores S. Morante A. Jardon
Improving CGDA execution through Genetic Algorithms incorporating Spatial and Velocity constraints
IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), 2017, Coimbra, Portugal
R. Fernandez-Fernandez D. Estévez Juan G. Victores
Reducing the Number of Evaluations Required for CGDA Execution through Particle Swarm Optimization Methods
IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), 2017, Coimbra, Portugal
R. Fernandez-Fernandez D. Estévez Juan G. Victores
Robot Imitation through Vision, Kinesthetic and Force Features with Online Adaptation to Changing Environments
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, Madrid, Spain
R. Fernandez-Fernandez Juan G. Victores D. Estévez

Entries:
Robocity16 Open Conference on Future Trends in Robotics
chapter: New trends and challenges in the automatic generation of new tasks for humanoid robots CSIC , ISBN: 978-84-608-8452-1, 2016
R. Fernandez-Fernandez Juan G. Victores C. Balaguer
Robocity16 Open Conference on Future Trends in Robotics
chapter: New trends and challenges in the automatic generation of new tasks for humanoid robots CSIC , ISBN: ISBN: 978-84-608-8452-1, 2016
R. Fernandez-Fernandez Juan G. Victores C. Balaguer

Entries:
Robot Imagination System
Universidad Carlos III de Madrid , 2014
Juan G. Victores

Previous Robot types & applications

next Robot types & applications