24 accepted papers
Recent research has seen the advancement of drone depot models as a promising way to allocate drones for large-scale task completion. Applications of these drone depot models include data collection, environmental monitoring, package delivery, and more. This paper focuses on sharing agents between s
This paper proposes a heterogeneous teaming solution to the problem of target discovery and monitoring in unknown, non-convex environments. The team consists of two types of agents: agile agents with sensors capable of mapping their surroundings and slower agents that are capable of monitoring or se
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 proposes a formulation for the risk-aware path planning problem which utilizes multi-objective optimization to dynamically plan trajectories that satisfy multiple complex mission specifications. In the setting of persistent monitoring, we develop a method for representing environmental in…
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…
This paper proposes an algorithm for generating Pareto-optimal privacy-aware trajectories for multi-robot coverage. Our approach utilizes a genetic algorithm to generate a set of modified trajectories for a team of robots that wishes to obscure its goal from an observer. A novel velocity-constrained…
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…
We apply a novel framework for decomposing and reasoning about free space in an environment to a multi-agent persistent monitoring problem. Our decomposition method represents free space as a collection of ellipsoids associated with a weighted connectivity graph. The same ellipsoids used for reasoni…
This paper presents a mobile UVC disinfection robot designed to mitigate the threat of airborne and surface pathogens. Our system comprises a mobile robot base, a custom UVC lamp assembly, and algorithms for autonomous navigation and path planning. We present a model of UVC disinfection and dosage o…
We address the problem of assigning a team of drones to autonomously capture a set desired shots of a dynamic target in the presence of obstacles. We present a two-stage planning pipeline that generates offline an assignment of drone to shots and locally optimizes online the viewpoint. Given desired…
The safety of an autonomous vehicle not only depends on its own perception of the world around it, but also on the perception and recognition from other vehicles. If an ego vehicle considers the uncertainty other vehicles have about itself, then by reducing the estimated uncertainty it can increase…
This paper investigates the safe path planning problem for an autonomous vehicle operating in unstructured, cluttered environments. While some objects may be accurately with canonical perception algorithms, other objects and clutter may be harder to track. We present an approach that combines two me…
This paper introduces the Weighted Buffered Voronoi tessellation, which allows us to define distributed, semicooperative multi-agent navigation policies with guarantees on collision avoidance. We generate the Voronoi cells with dynamic weights that bias the boundary towards the agent with the lower…
In this paper, we examine the problem of navigating cluttered environments without explicit object detection and tracking. We introduce the dynamic risk density to map the congestion density and spatial flow of the environment to a cost function for the agent to determine risk when navigating that e…
Among traffic accidents in the USA, 23% of fatal and 32% of non-fatal incidents occurred at intersections. For driver assistance systems, intersection navigation remains a difficult problem that is critically important to increasing driver safety. In this letter, we examine how to navigate an unsign
Current methods for autonomous management use strict first-come, first-serve (FCFS) ordering to manage incoming autonomous vehicles at an intersection. In this work, we present a coordination policy that swaps agent ordering to increase the system-wide performance while ensuring that the swaps are s…
In this paper, we address the problem of navigating in a cluttered environment by introducing a congestion cost that maps the density and motion of objects to an occupancy risk. We propose that an agent can choose a “risk level set” from this cost function and construct a planning space from this se…
We propose a distributed algorithm for the cooperative pursuit of multiple evaders using multiple pursuers in a bounded convex environment. The algorithm is suitable for intercepting rogue drones in protected airspace, among other applications. The pursuers do not know the evaders' policy, but by us
We investigate the cooperative pursuit of an evader by a group of quadrotors in an environment with no-fly zones. While the pursuers cannot enter into no-fly zones, the evader may freely move through zones to avoid capture. Once the evader enters a no-fly zone, the pursuers calculate a reachable set…
This paper proposes a new approach for a group of robots carrying out a collaborative task to adapt on-line to actuation performance variations among the robots. We consider the problem of multi-robot coverage, where a group of robots has to spread out to cover the environment. We suppose that some…
This paper presents a new control strategy to control a group of dog-like robots to drive a herd of non-cooperative sheep-like agents to a goal region in the environment. The sheep-like agents, which may be biological or robotic, respond to the presence of the dog-like robots with a repelling potent…