Papers
15
Total Citations
132
H-Index
8
About
Vijay Kumar Dalla is a prominent robotics researcher whose work focuses on space robotics, motion planning, and trajectory optimization for redundant and hyper-redundant manipulators. His research addresses some of the most pressing challenges in space robotics, including failure control, energy and power optimization, and collision-free trajectory planning for complex multi-link systems operating in harsh environments. Dalla's most cited work (22 citations) applies genetic algorithms to optimize failure control and energy efficiency in multi-axes space manipulators, while his research on hyper-redundant planar space robots (16 citations) pioneered curve-constrained, collision-free motion planning methodologies. His subsequent studies introduced advanced bio-inspired optimization techniques—including Grey-Wolf and Cuckoo Search algorithms—to achieve jerk-optimized and singularity-free motion planning, reflecting a consistent drive toward smarter, more efficient robotic control strategies. Beyond individual manipulators, Dalla has made notable contributions to cooperative space robotics, investigating multi-robot docking operations, impedance control for flexible wire manipulation, and space debris removal. His interdisciplinary reach is evident in a study exploring robotic solutions for COVID-19 (7 citations). With over 115 cumulative citations across his most recognized works, Dalla's research significantly advances the reliability and autonomy of robotic systems in space exploration and beyond.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4Power-optimized motion planning of reconfigured redundant space robot12 citations · 2018
- 5
- 6
- 7
- 8
- 9
- 10Combating COVID-19: Study of robotic solutions for COVID-197 citations · 2021