Feedback motion planning

MIT 6.821: Underactuated Robotics

Spring 2024, Lecture 23

Follow live at https://slides.com/d/v3rQ2yY/live
(or later at https://slides.com/russtedrake/spring24-lec23)

Image credit: Boston Dynamics

/// Base type for all action primitives
class ActionPrimitiveInterface
{
  virtual bool IsCandidate(const State& state) const = 0;
  virtual Container GetOutcomes(const State& state) const = 0;
  virtual double EstimateActionCost(
      const State& current, const State& target) const = 0;
  virtual Container Execute(const State& state) = 0;
  virtual double Ranking() const = 0;
};
OpenDishwasherDoor
CloseDishwasherDoor
StartDishwasher
LoadSoapPacket
PullOutLowerRack
PullOutUpperRack
PullOutSilverwareRack
PushInLowerRack
PushInUpperRack
PushInSilverwareRack
PutPlateInDishwasher
ReorientMug
PutMugInDishwasher
OptimisticPutMugInDishwasher
PutSilverwareInDishwasher
PushUnmanipulableDish
SenseDishCounts
SenseDishToManipulate

work by Calder Phillips-Grafflin et al. at TRI

DishTaskState(const DishState& active_dish_state,
              int32_t clean_items_put_away, int32_t clean_items_in_dishwasher,
              int32_t dirty_items_in_dishwasher,
              int32_t dirty_items_available,
              const DishwasherState& current_dishwasher_state);

DishState(const RigidTransformd& dish_pose, DishType dish_type,
          DishProgress dish_progress, RackRequirement rack_required);

DishwasherState(bool known, bool door_open, bool lower_rack_out,
                bool upper_rack_out, bool silverware_rack_out,
                bool lower_rack_full, bool upper_rack_full,
                bool silverware_rack_full, bool started, bool soap_loaded);
enum class DishType : uint8_t {
  Unknown = 0x00,
  Mug = 0x01,
  Plate = 0x02,
  Silverware = 0x03
};

enum class RackRequirement : uint8_t {
  Unknown = 0x00,
  LowerRack = 0x01,
  UpperRack = 0x02,
  SilverwareRack = 0x03
};
enum class DishProgress : uint8_t {
  Unknown = 0x00,
  Unmanipulable = 0x01,
  LikelyManipulable = 0x02,
  Sensed = 0x03,
  OptimisticOriented = 0x04,
  Oriented = 0x05,
  Placed = 0x06,
  Released = 0x07
};

work by Calder Phillips-Grafflin et al. at TRI

STRIPS problem definitions

https://en.wikipedia.org/wiki/Stanford_Research_Institute_Problem_Solver

  • Initial state
  • Goal state(s)
  • Set of actions. For each:
    • preconditions
    • effects
/// Base type for all action primitives
class ActionPrimitiveInterface
{
  virtual bool IsCandidate(const State& state) const = 0;
  virtual Container GetOutcomes(const State& state) const = 0;
  ...
};
  • PDDL (Planning Domain Definition Language)

Feedback via online replanning

In the dish-loading example, we replan before each action to handle unexpected outcomes...

RRT* (Karaman and Frazzoli)

Martin Buehler and Dan Koditschek

Al Rizzi and Dan Koditschek

Rob Burridge, Al Rizzi, and Dan Koditschek

Probabilistic Feedback Coverage

Lecture 23: Feedback motion planning

By russtedrake

Lecture 23: Feedback motion planning

MIT Underactuated Robotics Spring 2024 http://underactuated.csail.mit.edu

  • 229