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11. Geometric and numerical aspects of redundancy

Author

Dimitar Dimitrov, Adrien Escande, Pierre-Brice Wieber, Alexander Sherikov, Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems (BIPOP), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Joint Robotics Laboratory (CNRS-AIST JRL ), National Institute of Advanced Industrial Science and Technology (AIST)-Centre National de la Recherche Scientifique (CNRS), and Joint Robotics Laboratory [Japan] (CNRS-AIST JRL)

Subjects
0301 basic medicine, Engineering, Trust region, Mathematical optimization, business.industry, Mobile manipulator, Resolution (logic), Newton's method in optimization, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Singularity, 030220 oncology & carcinogenesis, Redundancy (engineering), Robot, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], Artificial intelligence, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], business, Humanoid robot
Abstract

International audience; If some resources of a robot are redundant with respect to a given objective, they can be used to address other, additional objectives. Since the amount of resources required to realize a given objective can vary, depending on the situation, this gives rise to a limited form of decision making, when assigning resources to different objectives according to the situation. Such decision making emerges in case of conflicts between objectives, and these conflicts appear to be situations of linear dependency and, ultimately, singularity of the solutions. Using an elementary model of a mobile manipulator robot with two degrees of freedom, we show how standard resolution schemes behave unexpectedly and inefficiently in such situations. We propose then as a remedy to introduce carefully tuned artificial conflicts, in the form of a trust region.

Published
2017
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12. Safe navigation strategies for a biped robot walking in a crowd

Author

Dimitar Dimitrov, Nestor Bohorquez, Alexander Sherikov, Pierre-Brice Wieber, Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems (BIPOP), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), and Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])

Subjects
0209 industrial biotechnology, Computer science, 02 engineering and technology, Collision, Mobile robot navigation, 020901 industrial engineering & automation, Crowds, Terminal (electronics), Control theory, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Robot, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], 020201 artificial intelligence & image processing, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Duration (project management), Simulation, Collision avoidance
Abstract

International audience; Safety needs to be guaranteed before we can introduce robots into our working environments. For a biped robot to navigate safely in a crowd it must maintain balance and avoid collisions. In highly dynamic and unpredictable environments like crowds, collision avoidance is usually interpreted as passive safety, i.e. that the robot can stop before any collision occurs. We show that both balance preservation and passive safety can be analyzed, from the point of view of viability theory, as the ability of the robot to stop safely at some point in the future. This allows us to address both problems with a single model predictive controller with appropriate terminal constraints. We demonstrate that this controller predicts failures (falls and collisions) as early as the duration of the preview horizon. Finally, we propose a new strategy for safe navigation that relaxes the passive safety conditions to allow the robot to avoid a greater number of collisions.

Published
2016
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13. A Newton method with always feasible iterates for Nonlinear Model Predictive Control of walking in a multi-contact situation

Author

Pierre-Brice Wieber, Dimitar Dimitrov, Diana Serra, Alexander Sherikov, Camille Brasseur, Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione [Napoli] (DIETI), Università degli studi di Napoli Federico II, Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems (BIPOP), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), and University of Naples Federico II = Università degli studi di Napoli Federico II

Subjects
0209 industrial biotechnology, Mathematical optimization, Computer science, Computation, 020207 software engineering, 02 engineering and technology, Nonlinear control, symbols.namesake, Nonlinear system, Model predictive control, 020901 industrial engineering & automation, Control theory, Iterated function, 0202 electrical engineering, electronic engineering, information engineering, symbols, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Reduction (mathematics), Dynamic balance, Newton's method
Abstract

International audience; In this paper, we present a Nonlinear Model Predictive Control scheme, which is able to generate walking motions in multi-contact situations. Walking up and down stairs with an additional hand support is a typical example, which we address in simulation. Computing such a nonlinear control scheme is usually done with a Newton method, a potentially time-consuming procedure involving iterative linearizations. We propose here a Newton method which is specifically designed to provide at each iteration a feasible solution, always satisfying the (nonlinear) dynamic balance constraints. This results in a significant reduction in computation time, by minimizing the number of necessary iterations to reach a feasible solution.

Published
2016
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14. A hierarchical approach to minimum-time control of industrial robots

Author

Alexander Sherikov, Saed Al Homsi, Dimitar Dimitrov, Pierre-Brice Wieber, Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems (BIPOP), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), and Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])

Subjects
0209 industrial biotechnology, Engineering, Optimization problem, business.industry, SCARA, Control engineering, Robotics, 02 engineering and technology, Robot control, Model predictive control, 020901 industrial engineering & automation, Control theory, 0202 electrical engineering, electronic engineering, information engineering, SMT placement equipment, Robot, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], 020201 artificial intelligence & image processing, Artificial intelligence, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], business, Reactive system
Abstract

International audience; A novel approach to minimum-time control is presented. It is stated in terms of a hierarchical optimization problem, which is standard in the field of robotics. This is advantageous as already existing tools can be used to approach its solution. Our formulation is applied to the online generation of trajectories for industrial robots performing pick and place operations in the presence of obstacles. Model predictive control is used in order to achieve reactive system behavior and to obtain accurate local approximations of the collision avoidance constraints (which are nonconvex). Our approach has the capacity to suppress high frequency chattering in the control signal in the presence of noise: a common drawback of aggressive control strategies. Experiment using two SCARA robots that share the same working environment is used to evaluate the presented approach.

Published
2016
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15. Walking pattern generators designed for physical collaboration

Author

Pierre-Brice Wieber, Don Joven Agravante, Alexander Sherikov, Abderrahmane Kheddar, Andrea Cherubini, Interactive Digital Humans (IDH), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems (BIPOP), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Joint Robotics Laboratory [Japan] (CNRS-AIST JRL), National Institute of Advanced Industrial Science and Technology (AIST)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-National Institute of Advanced Industrial Science and Technology (AIST), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), and Joint Robotics Laboratory (CNRS-AIST JRL )

Subjects
0209 industrial biotechnology, Engineering, Model-predictive control, business.industry, Carry (arithmetic), Control engineering, 02 engineering and technology, Physical interaction, Construct (python library), Reduced model, Model predictive control, 020901 industrial engineering & automation, Human-humanoid physical interaction, 0202 electrical engineering, electronic engineering, information engineering, Humanoid walking, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], 020201 artificial intelligence & image processing, business, Simulation, Humanoid robot
Abstract

International audience; This paper is about the design of humanoid walking pattern generators to be used for physical collaboration. A particular use case is a humanoid robot helping a human to carry large and/or heavy objects. To do this, we construct a reduced model which takes into account physical interaction. This is used in a model predictive control framework to generate separate behaviors for being a follower or a leader. The approach is then validated both on simulation and on the HRP-4 humanoid robot.

Published
2016
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16. Balancing a humanoid robot with a prioritized contact force distribution

Author

Pierre-Brice Wieber, Alexander Sherikov, Dimitar Dimitrov, Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems (BIPOP), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), and Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)

Subjects
0209 industrial biotechnology, Computer science, Constraint (computer-aided design), Motion controller, 02 engineering and technology, Contact force, Acceleration, Task (computing), 020901 industrial engineering & automation, Control theory, 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], Robot, 020201 artificial intelligence & image processing, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Humanoid robot
Abstract

International audience; Humanoid robots propel themselves and perform tasks by interacting with their environment through contact forces. Typically, nonuniqueness of these forces is dealt with by distributing them evenly between the contacts. In the present paper, we introduce strict prioritization in contact force distribution, to reflect situations when an application of certain contact forces should be avoided as much as possible, for example, due to a fragility of the support. We illustrate this by designing a whole body motion controller for a setting with multiple noncoplanar contacts, where application of an optional contact force is allowed only if it is necessary to maintain balance and execute a task. Balance preservation is addressed by imposing a capturability constraint based on anticipation with a linear model adapted to multiple noncoplanar contacts. The controller is evaluated in simulations.

Published
2015
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17. Whole body motion controller with long-term balance constraints

Author

Dimitar Dimitrov, Alexander Sherikov, Pierre-Brice Wieber, Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems (BIPOP), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), and Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)

Subjects
0209 industrial biotechnology, Robot kinematics, Computer science, Motion controller, 02 engineering and technology, Motion (physics), 020901 industrial engineering & automation, Control theory, Position (vector), Obstacle avoidance, 0202 electrical engineering, electronic engineering, information engineering, Robot, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], 020201 artificial intelligence & image processing, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Humanoid robot
Abstract

International audience; The standard approach to real-time control of humanoid robots relies on approximate models to produce a motion plan, which is then used to control the whole body. Separation of the planning stage from the controller makes it difficult to account for the whole body motion objectives and constraints in the plan. For this reason, we propose to omit the planning stage and introduce long-term balance constraints in the whole body controller to compensate for this omission. The new controller allows for generation of whole body walking motions, which are automatically decided based on both the whole body motion objectives and balance preservation constraints. The validity of the proposed approach is demonstrated in simulation in a case where the walking motion is driven by a desired wrist position. This approach is general enough to allow handling seamlessly various whole body motion objectives, such as desired head motions, obstacle avoidance for all parts of the robot, etc.

Published
2014
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18. A sparse model predictive control formulation for walking motion generation

Author

Alexander Sherikov, Dimitar Dimitrov, Pierre-Brice Wieber, Örebro University, Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems (BIPOP), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), and Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)

Subjects
Hessian matrix, 0209 industrial biotechnology, Optimization problem, Discretization, 02 engineering and technology, Sparse approximation, Model predictive control, symbols.namesake, 020901 industrial engineering & automation, Control theory, 0202 electrical engineering, electronic engineering, information engineering, symbols, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], 020201 artificial intelligence & image processing, Quadratic programming, Mathematics, Sparse matrix, Computer technology
Abstract

International audience; This article presents a comparison between dense and sparse model predictive control (MPC) formulations, in the context of walking motion generation for humanoid robots. The former formulation leads to smaller, the latter one to larger but more structured optimization problem. We put an accent on the sparse formulation and point out a number of advantages that it presents. In particular, motion generation with variable center of mass (CoM) height, as well as variable discretization of the preview window, come at a negligible additional computational cost. We present a sparse formulation that comprises a diagonal Hessian matrix and has only simple bounds (while still retaining the possibility to generate motions for an omnidirectional walk). Finally, we present the results from a customized code used to solve the underlying quadratic program (QP).

Published
2011
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