collaborators

10 papers

cs.AI2026

Front-to-Attractors: Modifying the Front-to-Front Heuristic in Bidirectional Search

Alvin Zou, Muhammad Suhail Saleem, Maxim Likhachev

Heuristics play a central role in the performance of bidirectional search algorithms, which commonly rely on two main classes. Front-to-end (F2E) heuristics estimate the distance f…

cs.RO2025

A Contact-Driven Framework for Manipulating in the Blind

Muhammad Suhail Saleem, Lai Yuan, Maxim Likhachev

Robots often face manipulation tasks in environments where vision is inadequate due to clutter, occlusions, or poor lighting--for example, reaching a shutoff valve at the back of a…

cs.AI2025

A-MHA*: Anytime Multi-Heuristic A*

Ramkumar Natarajan, Muhammad Suhail Saleem, William Xiao +3

Designing good heuristic functions for graph search requires adequate domain knowledge. It is often easy to design heuristics that perform well and correlate with the underlying tr…

cs.RO2025

Learning Local Heuristics for Search-Based Navigation Planning

Rishi Veerapaneni, Muhammad Suhail Saleem, Maxim Likhachev

Graph search planning algorithms for navigation typically rely heavily on heuristics to efficiently plan paths. As a result, while such approaches require no training phase and can…

cs.RO2025

Lazy Heuristic Search for Solving POMDPs with Expensive-to-Compute Belief Transitions

Muhammad Suhail Saleem, Rishi Veerapaneni, Maxim Likhachev

Heuristic search solvers like RTDP-Bel and LAO* have proven effective for computing optimal and bounded sub-optimal solutions for Partially Observable Markov Decision Processes (PO…

cs.MA2025

Windowed MAPF with Completeness Guarantees

Rishi Veerapaneni, Muhammad Suhail Saleem, Jiaoyang Li +1

Traditional multi-agent path finding (MAPF) methods try to compute entire start-goal paths which are collision free. However, computing an entire path can take too long for MAPF sy…