Tool force adaptation in soil-digging task for humanoid robot

Simultaneous control of position and force of robots is one of the difficult and important problems in the field of robotics. Even if we can get a desirable positional trajectory of robots' end effectors or tools that they use, it is not easy to know how much force we should apply in order to execute planned tasks. We propose a method that enables robots to exert the required force to successfully carry out tasks. In this paper, we introduce a method to realize online updating of the force applied to the environment through tools and modification of Center of Gravity (CoG) based on the reference force. The update direction of the force is set in advance considering the interaction between tools and environment. We take manipulation of a shovel as an example. To verify the effect of our method, a humanoid robot JAXON demonstrates the soil-digging task under various conditions.

[1]  Stefan Schaal,et al.  Dynamics systems vs. optimal control--a unifying view. , 2007, Progress in brain research.

[2]  Sanjiv Singh,et al.  The State of the Art in Automation of Earthmoving , 1997 .

[3]  Alberto Montebelli,et al.  On handing down our tools to robots: Single-phase kinesthetic teaching for dynamic in-contact tasks , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[4]  Jun Nakanishi,et al.  Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors , 2013, Neural Computation.

[5]  Darwin G. Caldwell,et al.  Imitation Learning of Positional and Force Skills Demonstrated via Kinesthetic Teaching and Haptic Input , 2011, Adv. Robotics.

[6]  M. A. Arbib,et al.  Models of Trajectory Formation and Temporal Interaction of Reach and Grasp. , 1993, Journal of motor behavior.

[7]  Masayuki Inaba,et al.  Humanoid full-body controller adapting constraints in structured objects through updating task-level reference force , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Leonhard E. Bernold,et al.  Experimental Studies on Mechanics of Lunar Excavation , 1991 .

[9]  Laurent Philippe,et al.  Using GPU for Multi-Agent Soil Simulation , 2013, 2013 21st Euromicro International Conference on Parallel, Distributed, and Network-Based Processing.

[10]  Shuuji Kajita,et al.  Pushing manipulation by humanoid considering two-kinds of ZMPs , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[11]  Sanjiv Singh.  The State of the Art in Automation of Earthmoving , 1997 .

[12]  Ian R. Manchester,et al.  Combined ILC and Disturbance Observer for the Rejection of Near-Repetitive Disturbances, With Application to Excavation , 2015, IEEE Transactions on Control Systems Technology.

[13]  Darwin G. Caldwell,et al.  Challenges for the policy representation when applying reinforcement learning in robotics , 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

[14]  Atsushi Konno,et al.  Working postures for humanoid robots to generate large manipulation force , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[15]  Alberto Montebelli,et al.  Simultaneous kinesthetic teaching of positional and force requirements for sequential in-contact tasks , 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

[16]  Masayuki Inaba,et al.  Development of life-sized high-power humanoid robot JAXON for real-world use , 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).