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5 results on '"Alexander Sherikov"'

1. Human-Humanoid Collaborative Carrying

Author

Don Joven Agravante, Abderrahmane Kheddar, Alexander Sherikov, Andrea Cherubini, Pierre-Brice Wieber, 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), PAL Robotics, Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria), Joint Robotics Laboratory [Japan] (CNRS-AIST JRL), 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), Joint Robotics Laboratory (CNRS-AIST JRL ), and National Institute of Advanced Industrial Science and Technology (AIST)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0209 industrial biotechnology, Robot kinematics, Task-space optimization control, Computer science, Physical Human-Robot Interaction, 02 engineering and technology, Motion (physics), Field (computer science), Computer Science Applications, Variety (cybernetics), [SPI.AUTO]Engineering Sciences [physics]/Automatic, Human and humanoid skills/interaction, 020901 industrial engineering & automation, Constrained optimization problem, Humanoid robotics, Control and Systems Engineering, Human–computer interaction, Task analysis, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], Electrical and Electronic Engineering, Humanoid robot
Abstract

International audience; This paper contributes to the field of physical human-robot collaboration. We present a complete control framework, which aims at making humanoid robots capable of carrying objects together with humans. First, we design a template identifying the primitive subtasks necessary for collaborative carrying. Then, these subtasks are formulated as constrained optimization problems for controlling the whole-body motion of a humanoid robot. The subtasks include two walking pattern generators that account for physical collaboration, as well as posture and grasping controllers. Finally, we validate our framework in a variety of collaborative carrying experiments, using the HRP-4 humanoid robot.

Published
2019
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2. 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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3. 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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4. 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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5. 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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