ADVRHumanoids/casannis_walking

[Payload]Next steps for the payload transportation work

Closed this issue · 3 comments

  • Try to penalize deviation of hands from nominal position over the whole trajectory. Then try to express the fraction of the weights of the CoM and hands penalizations. The target is that the user be able to regulate the trade-off between CoM and hands movement with a single weight depending on the task.
  • Try to formulate a TO problem where the workspace of the hands is both forward and backward of the robot's torso. Two cases I can think is: 1) add constraint that the distance between hand and torso center be greater than something (in this case there is need to express torso center wrt to CoM somehow), 2) set box constraint for each hand that is after the respective shoulder (and maybe higher, at the height of head) so that there is no self collision and constraint is convex.
  • There is need to express the results and benefits of our method quantitavely. This may be done by traversing a slope where before was not possible to traverse, or to express somehow the reduced kinematic stretching of the legs.
  • Add friction cones and check how they affect the current formulation
  • Check how the idea applies to other nlp (towr etc.)
  • Access joint trajectories of lower body to compare and show leg stretching
  • Optimize different force at each arm and make the formulation more general.
  • Penalizing payload acceleration (analytical cost) may not be necessary.

Summarize:

  • Try to formulate a TO problem where the workspace of the hands is both forward and backward of the robot's torso. Two cases I can think is: 1) add constraint that the distance between hand and torso center be greater than something (in this case there is need to express torso center wrt to CoM somehow), 2) set box constraint for each hand that is after the respective shoulder (and maybe higher, at the height of head) so that there is no self collision and constraint is convex.
  • Check how the idea applies to other nlp (towr etc.)
  • Optimize different force at each arm and make the formulation more general. -> optimization time increases (almost double)
  • Penalizing payload acceleration (analytical cost) may not be necessary.
  • Check maybe the force and/or jerk at last knot is not needed to be optimized