Consider the task of setting a dinner table. It involves placing the appropriate serving utensils and silverware according to the dishes being served. Some of the objects need to be placed in a particular order as they might be stacked on top of each other or due to cultural traditions. Many real-world tasks demonstrate such […]
A recent paper by Xi Yu and M. Ani Hsieh from the University of Pennsylvania presents a distributed control and coordination strategy that allows a swarm of mobile robots to form an intermittently connected communication network as they monitor a given environment. The approach assumes robots are tasked to patrol a set of perimeters in […]
A recent paper by members of the DCIST alliance develops a method for distributed control of large networks of mobile robots with interacting dynamics and sparsely available communications. Their approach is to learn local controllers that require only local information and communications at test time by imitating the policy of centralized controllers using global information […]
Surveillance of perimeters and securing perimeters are important tasks in civilian and military defense applications, and it has become practical to deploy a large number of autonomous agents to address these problems using multi-robot systems. A recent paper by members of the DCIST alliance formulates this scenario as a variant of multi-player pursuit-evasion games, where […]
In this work, we study the structure of real-world communication systems to understand how information can be rapidly and efficiently communicated to humans, for example from swarms of drones or other agents. Humans constantly receive information from systems of interconnected stimuli or concepts — from language and music to literature and science — yet it […]
In the future, teams of heterogeneous robot teams will be operating in unknown and adversarial environments. In failure prone or adversarial environments, the capability of resilience is crucial to ensuring the robots can complete their mission. Mission resilience to robot failures, sensor attacks or communication disruptions is currently an afterthought leading to optimal over-provisioned designs. […]
While many distributed reinforcement learning (RL) has emerged as one of the important paradigms in distributed control, we are only beginning to understand the fundamental behavior of these algorithms. Two recent papers from the DCIST alliance provide important progress in this direction. In the multi-agent policy evaluation problem, a group of agents operate in a […]
To operate successfully in a complex and changing environment, learning agents must be able to acquire new skills quickly. Humans display remarkable skill in this area — we can learn to recognize a new object from one example, adapt to driving a different car in a matter of minutes, and add a new slang word […]
A recent paper by members of the DCIST alliance proposes an approach for building semantic maps, containing object poses and shapes, in real time, onboard an autonomous robot equippend with a monocular camera. Rich understanding of the geometry and context of a robot’s surroundigs is important for specification and safe, efficient execution of complex missions. This […]