Control architecture for the Belgrade/USC hand
Dextrous robot hands
Using MPI (2nd ed.): portable parallel programming with the message-passing interface
Using MPI (2nd ed.): portable parallel programming with the message-passing interface
Dynamically-Stable Motion Planning for Humanoid Robots
Autonomous Robots
Robonaut: A Robot Designed to Work with Humans in Space
Autonomous Robots
Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces
ACM SIGGRAPH 2004 Papers
On the Probabilistic Foundations of Probabilistic Roadmap Planning
International Journal of Robotics Research
A General Deterministic Sequence for Sampling d-Dimensional Configuration Spaces
Journal of Intelligent and Robotic Systems
Finding locally optimum force-closure grasps
Robotics and Computer-Integrated Manufacturing
Hand Posture Subspaces for Dexterous Robotic Grasping
International Journal of Robotics Research
Motion planning for high DOF anthropomorphic hands
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Manipulation planning on constraint manifolds
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Sampling-based path planning for geometrically-constrained objects
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Efficient search of obstacle-free paths for anthropomorphic hands
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Global manipulation planning in robot joint space with task constraints
IEEE Transactions on Robotics
Synthesizing grasp configurations with specified contact regions
International Journal of Robotics Research
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The paper deals with the problem of motion planning of anthropomorphic mechanical hands avoiding collisions and trying to mimic real human hand postures. The approach uses the concept of "principal motion directions" to reduce the dimension of the search space in order to obtain results with a compromise between motion optimality and planning complexity (time). Basically, the work includes the following phases: capturing the human hand workspace using a sensorized glove and mapping it to the mechanical hand workspace, reducing the space dimension by looking for the most relevant principal motion directions, and planning the hand movements using a probabilistic roadmap planner. The approach has been implemented for a four finger anthropomorphic mechanical hand (17 joints with 13 independent degrees of freedom) assembled on an industrial robot (6 independent degrees of freedom), and experimental examples are included to illustrate its validity.