Papers
3
Total Citations
57
H-Index
2
About
Mariam Kashkash is a leading researcher in robotics and artificial intelligence, specializing in path planning for mobile robots and manipulators in complex, dynamic environments. Her work focuses on developing bio-inspired and reinforcement learning algorithms to enable autonomous navigation. Her most influential contribution is the application of the Bees Algorithm for wheeled mobile robot path planning in indoor environments with static and dynamic obstacles, a paper that has garnered 30 citations and introduced a novel continuous configuration space representation. She further advanced the field by integrating Q-Learning with the Bees Algorithm to achieve highly optimized path planning, earning 25 citations for this hybrid approach. Most recently, Kashkash has explored deep reinforcement learning techniques—including Deep Q-Network and Actor-Critic methods—to optimize the path of a 7-DOF Kinova Jaco Assistive Robot arm, demonstrating her ability to tackle high-dimensional control problems. Her work bridges nature-inspired optimization and modern machine learning, making significant contributions to autonomous robotics. With a growing citation record and innovative methodologies, Kashkash is a rising figure in intelligent robotic navigation.
Research Focus
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Top Papers
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