activity
20182021
most citedMotion Planning for a Pair of Tethered Robots

10 citations · 15 across the 5 of their papers we have counts for

collaborators

14 papers

cs.RO202110 cited

Motion Planning for a Pair of Tethered Robots

Reza H. Teshnizi, Dylan A. Shell

Considering an environment containing polygonal obstacles, we address the problem of planning motions for a pair of planar robots connected to one another via a cable of limited le…

cs.RO2020

Accelerating combinatorial filter reduction through constraints

Yulin Zhang, Hazhar Rahmani, Dylan A. Shell +1

Reduction of combinatorial filters involves compressing state representations that robots use. Such optimization arises in automating the construction of minimalist robots. But exa…

cs.RO20204 cited

Planning to Chronicle

Hazhar Rahmani, Dylan A. Shell, Jason M. O'Kane

An important class of applications entails a robot monitoring, scrutinizing, or recording the evolution of an uncertain time-extended process. This sort of situation leads an inter…

cs.AI2020

Every Action Based Sensor

Grace McFassel, Dylan A. Shell

In studying robots and planning problems, a basic question is what is the minimal information a robot must obtain to guarantee task completion. Erdmann's theory of action-based sen…

cs.RO2020

Abstractions for computing all robotic sensors that suffice to solve a planning problem

Yulin Zhang, Dylan A. Shell

Whether a robot can perform some specific task depends on several aspects, including the robot's sensors and the plans it possesses. We are interested in search algorithms that tre…

math.OC2020

Experiments with Tractable Feedback in Robotic Planning under Uncertainty: Insights over a wide range of noise regimes (Extended Report)

Mohamed Naveed Gul Mohamed, Suman Chakravorty, Dylan A. Shell

We consider the problem of robotic planning under uncertainty. This problem may be posed as a stochastic optimal control problem, complete solution to which is fundamentally intrac…