1 citations · 1 across the 6 of their papers we have counts for
6 papers
Terrain-Aware Model Predictive Control of Heterogeneous Bipedal and Aerial Robot Coordination for Search and Rescue Tasks
Abdulaziz Shamsah, Jesse Jiang, Ziwon Yoon +2
Humanoid robots offer significant advantages for search and rescue tasks, thanks to their capability to traverse rough terrains and perform transportation tasks. In this study, we…
Bipedal Safe Navigation over Uncertain Rough Terrain: Unifying Terrain Mapping and Locomotion Stability
Kasidit Muenprasitivej, Jesse Jiang, Abdulaziz Shamsah +2
We study the problem of bipedal robot navigation in complex environments with uncertain and rough terrain. In particular, we consider a scenario in which the robot is expected to r…
LTL-D*: Incrementally Optimal Replanning for Feasible and Infeasible Tasks in Linear Temporal Logic Specifications
Jiming Ren, Haris Miller, Karen M. Feigh +2
This paper presents an incremental replanning algorithm, dubbed LTL-D*, for temporal-logic-based task planning in a dynamically changing environment. Unexpected changes in the envi…
Real-time Model Predictive Control with Zonotope-Based Neural Networks for Bipedal Social Navigation
Abdulaziz Shamsah, Krishanu Agarwal, Shreyas Kousik +1
This study addresses the challenge of bipedal navigation in a dynamic human-crowded environment, a research area that remains largely underexplored in the field of legged navigatio…
Socially Acceptable Bipedal Navigation: A Signal-Temporal-Logic- Driven Approach for Safe Locomotion
Abdulaziz Shamsah, Ye Zhao
Social navigation for bipedal robots remains relatively unexplored due to the highly complex, nonlinear dynamics of bipedal locomotion. This study presents a preliminary exploratio…
TimePool: Visually Answer "Which and When" Questions On Univariate Time Series
Tinghao Feng, Yueqi Hu, Jing Yang +4
When exploring time series datasets, analysts often pose "which and when" questions. For example, with world life expectancy data over one hundred years, they may inquire about the…