Singularity-robust task-priority redundancy resolution for real-time kinematic control of robot manipulators

By S. Chiaverini. 1997

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Citations in the corpus

Active learning of inverse models with intrinsically motivated goal exploration in robots (2013, positive): “ion methods. Using the pseudo-inverse of Moore-Penrose [2] to compute the pseudo-inverse J+() of the Jacobian J() in a vicinity b_ is thus sucient. Possible problems happening due to singularities [106, 28, 91] being bypassed by adding noise in the joint congurations (see [86] for a study about this”
Chaotic Phenomena and Fractional-Order Dynamics in the Trajectory Control of Redundant Manipulators (2002, background): “A direct consequence is that it is possible to generate internal motions that reconfigure the manipulator structure without changing the gripper position and orientation [59-62].”
Position-based kinematics for 7-DoF serial manipulators with global configuration control, joint limit and singularity avoidance (2018, background): “specific position and orientation [9], such as: singularities [10, 11, 12] and joint limits avoidance [13, 14, 15], obstacle avoidance [16, 17], minimise energy dissipation [18], enhance manipulability [19] and human-like motions [7, 20, 21].”
Closed-Loop Inverse Kinematics for Redundant Robots: Comparative Assessment and Two Enhancements (2015, methodology): “For online position-tracking problems, a variant of this method can be implemented as explained in [51] to avoid singularity issues.”
Kinematic Control of Platoons of Autonomous Vehicles (2006, unknown): “Soc., 1998.”
Hierarchical quadratic programming: Fast online humanoid-robot motion generation (2014, methodology): “This case is sometimes called an algorithmic singularity [Chiaverini, 1997].”
Learning Forward Models for the Operational Space Control of Redundant Robots (2010, background): “Finally, DeMers and Kreutz-Delgado (1997) includes the topology to bring ﬂexibilities in his redundant kinematic inverse model.”