17 accepted papers
Generative models have emerged as a powerful paradigm for AI planning, yet their performance remains constrained by training data distribution. One approach is to improve generated solutions during inference by scaling test-time compute. A more efficient alternative is to optimize the inferential pr…
We introduce the Block Rearrangement Problem (BRaP), a challenging component of large warehouse management which involves rearranging storage blocks within dense grids to achieve a goal state. We formally define the BRaP as a graph search problem. Building on intuitions from sliding puzzle problems,
Multi-agent coordination is crucial for reliable multi-robot navigation in shared spaces such as automated warehouses. In regions of dense robot traffic, local coordination methods may fail to find a deadlock-free solution. In these scenarios, it is appropriate to let a central unit generate a globa
Motion planning with simple objectives, such as collision-avoidance and goal-reaching, can be solved efficiently using modern planners. However, the complexity of the allowed tasks for these planners is limited. On the other hand, signal temporal logic (STL) can specify complex requirements, but STL
The increased popularity of Behavior Trees (BTs) in different fields of robotics requires efficient methods for learning BTs from data instead of tediously handcrafting them. Recent research in learning from demonstration reported encouraging results that this letter extends, improves and generalize
This paper deals with Multi-robot Trajectory Planning, that is, the problem of computing trajectories for multiple robots navigating in a shared space while minimizing for control energy. Approaches based on trajectory optimization can solve this problem optimally. However, such methods are hampered…
This paper addresses the problem of automating fleets of robots with non-holonomic dynamics. Previously studied methods either specialize in facets of this problem, that is, one or a combination of multi-robot goal allocation, motion planning, and coordination, and typically acrifice optimality and…
In order to let multiple robot manipulators cooperatively complete a sequence of tasks in a shared workspace under task execution uncertainty, this letter proposes a multi-robot task allocation framework for constantly assigning tasks to robots, while the interference among concurrent robot motions
We propose a loosely-coupled framework for integrated task assignment, motion planning, coordination and control of heterogeneous fleets of robots subject to non-cooperative tasks. The approach accounts for the important real-world requirement that tasks can be posted asynchronously. We exploit syst
A standing challenge in current intralogistics is to reliably, effectively, yet safely coordinate large-scale, heterogeneous multi-robot fleets without posing constraints on the infrastructure or unrealistic assumptions on robots. A centralized approach, proposed by some of the authors in prior work
Coordination is a core problem in multi-robot systems, since it is a key to ensure safety and efficiency. Both centralized and decentralized solutions have been proposed, however, most assume perfect communication. This letter proposes a centralized method that removes this assumption, and is suitab
The way in which humans behave, speak and interact is deeply influenced by their culture. For example, greeting is done differently in France, in Sweden or in Japan; and the average interpersonal distance changes from one cultural group to the other. In order to successfully coexist with humans, rob…
Social norms are the understandings that govern the behavior of members of a society. As such, they regulate communication, cooperation and other social interactions. Robots capable of reasoning about social norms are more likely to be recognized as an extension of our human society. However, norms…
We introduce a variant of the multi-vehicle routing problem which accounts for nonholonomic constraints and dense, dynamic obstacles, called MVRP-DDO. The problem is strongly motivated by an industrial mining application. This paper illustrates how MVRP-DDO relates to other extensions of the vehicle…
Reliable autonomous navigation is still a challenging problem for robots with simple and inexpensive hardware. A key difficulty is the need to maintain an internal map of the environment and an accurate estimate of the robot's position in this map. Recently, a stigmergic approach has been proposed i…
Real-world robotic systems have to perform reliably in uncertain and dynamic environments. State-of-the-art cognitive robotic systems use an abstract symbolic representation of the real world for high-level reasoning. Some aspects of the world, such as object dynamics, are inherently difficult to ca…
Plan-based robot control has to consider a multitude of aspects of tasks at once, such as task dependency, time, space, and resource usage. Hybrid planning is a strategy for treating them jointly. However, by incorporating all these aspects into a hybrid planner, its search space is huge by construc…