معرفی شرکت ها


dm-robotics-controllers-0.5.0


Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

توضیحات

Python bindings for dm_robotics/cpp/controllers
ویژگی مقدار
سیستم عامل -
نام فایل dm-robotics-controllers-0.5.0
نام dm-robotics-controllers
نسخه کتابخانه 0.5.0
نگهدارنده []
ایمیل نگهدارنده []
نویسنده DeepMind
ایمیل نویسنده -
آدرس صفحه اصلی https://github.com/deepmind/dm_robotics/tree/main/cpp/controllers_py
آدرس اینترنتی https://pypi.org/project/dm-robotics-controllers/
مجوز Apache 2.0
# DM Robotics: Controllers Library (Python) Contents: - [Cartesian 6D to Joint Velocity Mapper](#Cartesian-6D-to-Joint-Velocity-Mapper) ## Cartesian 6D to Joint Velocity Mapper Python bindings for `dm_robotics/controllers/lsqp/cartesian_6d_to_joint_velocity_mapper`. This module consists of two classes: * `cartesian_6d_to_joint_velocity_mapper.Parameters` * `cartesian_6d_to_joint_velocity_mapper.Mapper` The mapper solves a constrained linear least-squares optimization problem at every iteration to compute the joint velocities that best achieve the desired Cartesian 6D velocity of an object. In its most basic configuration, it computes the joint velocities that achieve the desired Cartesian 6d velocity with singularity robustness. In addition, this mapper also supports the following functionality: * Nullspace control can be enabled to bias the joint velocities to a desired value without affecting the accuracy of the resultant Cartesian velocity; * Collision avoidance can be enabled between any two MuJoCo geoms; * Limits on the joint positions, velocities, and accelerations can be defined to ensure that the computed joint velocities do not result in limit violations. Please refer to `dm_robotics/controllers/lsqp/cartesian_6d_to_joint_velocity_mapper.h` or the class docstrings for more information. Dependencies: - dm_robotics/least_squares_qp - dm_robotics/controllers - [dm_control](https://github.com/deepmind/dm_control) ### Usage ```python from dm_control import mujoco from dm_control.mujoco.wrapper.mjbindings import enums from dm_robotics.controllers import cartesian_6d_to_joint_velocity_mapper # Initialize simulation. Assumes velocity controlled robot. # physics.data.ctrl[:] is an array of size 7 that corresponds to the commanded # velocities of the joints with IDs 7, 8, 9, 10, 12, 13, 14. physics = mujoco.Physics(...) # Create MuJoCo physics. # Create mapper parameters. params = cartesian_6d_to_joint_velocity_mapper.Parameters() # # Set model parameters. params.model = physics.model params.joint_ids = [7, 8, 9, 10, 12, 13, 14] # MuJoCo joint IDs being controlled. params.object_type = enums.mjtObj.mjOBJ_SITE # MuJoCo object being controlled. params.object_name = "end_effector" # name of MuJoCo object being controlled. params.integration_timestep = 0.005 # Amount of time the joint velocities will be executed for. # # Enable joint position limit constraint. Limits are read automatically from the # model. params.enable_joint_position_limits = True params.joint_position_limit_velocity_scale = 0.95 params.minimum_distance_from_joint_position_limit = 0.01 # ~0.5deg. # # Enable joint velocity limits. params.enable_joint_velocity_limits = True params.joint_velocity_magnitude_limits = [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] # # Enable joint acceleration limits. params.enable_joint_acceleration_limits = True params.remove_joint_acceleration_limits_if_in_conflict = True params.joint_acceleration_magnitude_limits = [10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0] # # Enable collision avoidance between the following geoms: # * "gripper" and "base_link" # * "base_link" and "floor" # * "link1" and "floor" # * "gripper" and "floor" # * "link1" and "link4" # * "link1" and "link5" # * "link1" and "link6" # * "link2" and "link4" # * "link2" and "link5" # * "link2" and "link6" # Note that collision avoidance will not be enabled for a pair of geoms if they # are attached to the same body or are attached to bodies that have a # parent-child relationship. params.enable_collision_avoidance = True params.collision_avoidance_normal_velocity_scale = 0.5 params.minimum_distance_from_collisions = 0.01 params.collision_detection_distance = 0.3 params.collision_pairs = [(["gripper"], ["base_link"]), (["base_link", "link1", "gripper"], ["floor"]), (["link1", "link2"], ["link4", "link5", "link6"])] # # Numerical stability parameters. params.check_solution_validity = True params.solution_tolerance = 1e-3 params.regularization_weight = 1e-2 params.enable_nullspace_control = True params.return_error_on_nullspace_failure = False params.nullspace_projection_slack = 1e-7 # Create mapper. mapper = cartesian_6d_to_joint_velocity_mapper.Mapper(params) # Compute joint velocities and apply them to the joint velocity actuator # commands at every step. while True: # The nullspace bias is often chosen to be a velocity towards the mid-range of # the joints, but can be chosen to be any 7D joint velocity vector. nullspace_joint_velocity_bias = get_nullspace_bias() target_cartesian_velocity = get_end_effector_target_velocity() solution = mapper.compute_joint_velocities(physics.data, target_velocity, nullspace_bias) physics.data.ctrl[:] = solution physics.step() ```


زبان مورد نیاز

مقدار نام
>=3.7, <3.11 Python


نحوه نصب


نصب پکیج whl dm-robotics-controllers-0.5.0:

    pip install dm-robotics-controllers-0.5.0.whl


نصب پکیج tar.gz dm-robotics-controllers-0.5.0:

    pip install dm-robotics-controllers-0.5.0.tar.gz