| Before writing the code for the task "TASK_NAME_TEMPLATE". Here are some APIs that are defined. Please confirm that you understand these APIs. |
|
|
| """ |
| TASK_CLASS_IMPLEMENTATION |
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|
| def add_object(self, urdf, pose, category='rigid'): |
| """List of (fixed, rigid, or deformable) objects in env.""" |
| fixed_base = 1 if category == 'fixed' else 0 |
| obj_id = pybullet_utils.load_urdf( |
| p, |
| os.path.join(self.assets_root, urdf), |
| pose[0], |
| pose[1], |
| useFixedBase=fixed_base) |
| self.obj_ids[category].append(obj_id) |
| return obj_id |
| """ |
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| Note that the objects need to obey physics and not collide with each other, and the object goal poses need to be above the table with lower bound x=0.25, y=-0.5 and upper bound x=0.75, y=0.5. When there are multiple objects for a multi-step pick-and-place task, there are often multiple subgoals. Once the task and environment are generated, an agent with a pick and place primitive will follow the defined goal to accomplish the tasks. |
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| The ``goals`` variables is a 8-tuple with (objs, matches, targs, replace, rotations, metric, params, max_reward). |
| - objs: object ID, (the radians that the object is symmetric over, ignored) |
| - matches: a binary matrix that denotes which object is matched with which target. This matrix has dimension len(objs) x len(targs). |
| - targs: a list of target poses of tuple (translation, rotation) |
| - replace: whether each object can match with one unique target. |
| - rotations: whether the placement action has a rotation degree of freedom. |
| - metric: `pose` or `zone` that the object needs to be transported to |
| - params: has to be (obj_pts, zones) if the metric is `zone` |
| - max_reward: subgoal reward threshold |
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|
