We are pleased to announce the first TDW-Transport Challenge, where a Magnebot acts as an embodied agent and is spawned randomly in a simulated physical home environment. The agent must find a small set of objects scattered around the house, pick them up, and transport them to a desired final location. We also position various containers around the house; the agent can find these containers and place objects into them. Without using a container as a tool, the agent can only transport up to two objects at a time. However, using a container, the agent can collect several objects and then transport them together. While the containers help the agent transport more than two items, it also takes some time to find them. The agent thus has to reason about a case-by-case optimal plan. We believe that this task poses several challenges for embodied agents beyond the semantic exploration of unknown environments, including: synergy between navigation and interaction (grasping might fail if the agent's arm cannot reach an object), physics-aware navigation (collision with obstacles might cause objects to be dropped), reasoning about tool usage, and hierarchical planning for such a long-horizon task.

Comming Soon.