6 papers
Non-Prehensile Multi-Object Placement with Mobile Robots via Diffusion-Based Trajectory Planning
Lance Pharand, Megnath Ramesh, Mark Chiu +2
Non-prehensile manipulation with mobile robots has primarily targeted placement in coarse goal regions. Precision placement has been studied with manipulators on benchmarks such as…
Bench-Push: Benchmarking Pushing-based Navigation and Manipulation Tasks for Mobile Robots
Ninghan Zhong, Steven Caro, Megnath Ramesh +3
Mobile robots are increasingly deployed in cluttered environments with movable objects, posing challenges for traditional methods that prohibit interaction. In such settings, the m…
Bench-NPIN: Benchmarking Non-prehensile Interactive Navigation
Ninghan Zhong, Steven Caro, Avraiem Iskandar +2
Mobile robots are increasingly deployed in unstructured environments where obstacles and objects are movable. Navigation in such environments is known as interactive navigation, wh…
Approximate Environment Decompositions for Robot Coverage Planning using Submodular Set Cover
Megnath Ramesh, Frank Imeson, Baris Fidan +1
In this paper, we investigate the problem of decomposing 2D environments for robot coverage planning. Coverage path planning (CPP) involves computing a cost-minimizing path for a r…
Anytime Replanning of Robot Coverage Paths for Partially Unknown Environments
Megnath Ramesh, Frank Imeson, Baris Fidan +1
In this paper, we propose a method to replan coverage paths for a robot operating in an environment with initially unknown static obstacles. Existing coverage approaches reduce cov…
Optimal Partitioning of Non-Convex Environments for Minimum Turn Coverage Planning
Megnath Ramesh, Frank Imeson, Baris Fidan +1
In this paper, we tackle the problem of planning an optimal coverage path for a robot operating indoors. Many existing approaches attempt to discourage turns in the path by coverin…