6 accepted papers
When agents in a multi-robot team have limited knowledge about their relative performance, their teammates, or the environment, robots must observe individual performance variations and adapt accordingly. We propose robot reputation to assess the historical performance of agents and make future adap…
This paper presents a method to reduce computations for stochastic dynamic games with game-theoretic belief space planning through partially propagating beliefs. Complex interactions in scenarios such as surveillance, herding, and racing can be modeled using game-theoretic frameworks in the belief s…
In this work, we consider a team of heterogeneous robots equipped with various types and quantities of resources, and tasked with supplying these resources to multiple dynamic demand locations. We present an adaptive control policy that enables robots to serve a dynamic demand: we allow demand to de…
We consider a team of heterogeneous robots, each equipped with various types and quantities of resources, and tasked with supplying these resources to multiple areas of demand. We propose a Voronoi-based coverage control approach to deploy robots to areas of demand by defining a position- and time-v…
We propose a co-navigation algorithm that enables a human and a robot to work together to navigate to a common goal. In this system, the human is responsible for making high-level steering decisions, and the robot, in turn, provides haptic feedback for collision avoidance and path suggestions while…
We propose a collaborative teleoperation algorithm which utilizes haptic force feedback to guide users around oncoming obstacles while accounting for non-holonomic constraints. The proposed algorithm predicts the user's goal, plans a path using a modified RRT* algorithm to the predicted goal, and pr…