full_chain.py

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# author: Vijay Pradeep

# A convenience object that wraps a dh_chain, along with transforms
# before and after the chain.
#
# The transforms can be thought of as follows:
#
#       before_chain_T[0] ... before_chain_T[N] -- chain -- after_chain_T[0] ... after_chain_T[N]
#      /
#   root

from sensor_msgs.msg import JointState
from numpy import matrix
import numpy


class FullChainRobotParams:

    # Initialize with dictionary of the current configuration.
    # Dictionary should have the following:
    #   - before_chain: List of transform ids to apply before the chain
    #   - chain_id: Chain ID for the dh_chain
    #   - dh_link_num: Specifies which dh elem should be the last one to apply.
    #   - after_chain: List of transform ids to apply after the chain
    def __init__(self, config_dict):
        self._config_dict = config_dict
        self.calc_block = FullChainCalcBlock()

    def update_config(self, robot_params):
        before_chain_Ts = [robot_params.transforms[transform_name] for transform_name in self._config_dict["before_chain"]]
        chain           = robot_params.dh_chains[ self._config_dict["chain_id"] ]
        dh_link_num     = self._config_dict["dh_link_num"]
        after_chain_Ts  = [robot_params.transforms[transform_name] for transform_name in self._config_dict["after_chain"]]
        self.calc_block.update_config(before_chain_Ts, chain, dh_link_num, after_chain_Ts)

class FullChainCalcBlock:
    def update_config(self, before_chain_Ts, chain, dh_link_num, after_chain_Ts):
        self._before_chain_Ts = before_chain_Ts
        self._chain = chain
        self._dh_link_num = dh_link_num
        self._after_chain_Ts = after_chain_Ts

    def fk(self, chain_state):
        pose = matrix(numpy.eye(4))

        # Apply the 'before chain' transforms
        for before_chain_T in self._before_chain_Ts:
            pose = pose * before_chain_T.transform

        # Apply the DH Chain
        dh_T = self._chain.fk(chain_state, self._dh_link_num)
        pose = pose * dh_T

        # Apply the 'after chain' transforms
        for after_chain_T in self._after_chain_Ts:
            pose = pose * after_chain_T.transform

        return pose

---

pr2_calibration_estimation
Author(s): Vijay Pradeep
autogenerated on Fri Jan 11 09:09:33 2013