A Lie group formulation of robot dynamics
International Journal of Robotics Research
Modeling, Identification and Control of Robots
Modeling, Identification and Control of Robots
Mathematical Programming: Series A and B
Continuous collision detection for articulated models using Taylor models and temporal culling
ACM SIGGRAPH 2007 papers
Potential field guide for humanoid multicontacts acyclic motion planning
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Fast C1proximity queries using support mapping of sphere-torus-patches bounding volumes
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Contact planning for acyclic motion with tasks constraints
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Multi-modal Motion Planning in Non-expansive Spaces
International Journal of Robotics Research
Compliant control of multicontact and center-of-mass behaviors in humanoid robots
IEEE Transactions on Robotics
Newton-Type Algorithms for Dynamics-Based Robot Movement Optimization
IEEE Transactions on Robotics
Dynamics and balance of a humanoid robot during manipulation tasks
IEEE Transactions on Robotics
Full-Body Compliant Human–Humanoid Interaction: Balancing in the Presence of Unknown External Forces
IEEE Transactions on Robotics
Planning and Fast Replanning Safe Motions for Humanoid Robots
IEEE Transactions on Robotics
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We propose a method to plan optimal whole-body dynamic motion in multi-contact non-gaited transitions. Using a B-spline time parameterization for the active joints, we turn the motion-planning problem into a semi-infinite programming formulation that is solved by nonlinear optimization techniques. Our main contribution lies in producing constraint-satisfaction guaranteed motions for any time grid. Indeed, we use Taylor series expansion to approximate the dynamic and kinematic models over fixed successive time intervals, and transform the problem (constraints and cost functions) into time polynomials which coefficients are function of the optimization variables. The evaluation of the constraints turns then into computation of extrema (over each time interval) that are given to the solver. We also account for collisions and self-collisions constraints that have not a closed-form expression over the time. We address the problem of the balance within the optimization problem and demonstrate that generating whole-body multi-contact dynamic motion for complex tasks is possible and can be tractable, although still time consuming. We discuss thoroughly the planning of a sitting motion with the HRP-2 humanoid robot and assess our method with several other complex scenarios.