Papers
13
Total Citations
289
H-Index
7
About
Junior Costa de Jesus is a prominent robotics and artificial intelligence researcher whose work sits at the intersection of deep reinforcement learning and autonomous robot navigation. His research has made significant strides in enabling mobile robots and unmanned aerial vehicles (UAVs) to navigate complex environments without relying on pre-built maps — a paradigm known as mapless navigation. His most influential contribution, "Soft Actor-Critic for Navigation of Mobile Robots" (2021), has garnered 93 citations, establishing him as a leading voice in applying stochastic deep reinforcement learning to real-world robotics challenges. Alongside earlier work on Deep Deterministic Policy Gradient techniques for mobile robots (51 citations), his research demonstrates a sustained and evolving exploration of both deterministic and stochastic approaches to robot motion control. Expanding beyond ground robots, Jesus pioneered deep reinforcement learning frameworks for UAV navigation, including innovative work on hybrid aerial-underwater vehicles and double critic architectures. His contributions to social robotics, including the Jubileo simulation framework and virtual reality platforms for human-robot interaction, reveal a researcher whose interests span the full breadth of modern robotics. With over 270 cumulative citations, his body of work continues to shape how autonomous systems learn to navigate and interact in dynamic, real-world environments.
Research Focus
Key Achievements
Top Papers
- 1Soft Actor-Critic for Navigation of Mobile Robots93 citations · 2021
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- 5Deep Deterministic Policy Gradient for Navigation of Mobile Robots18 citations · 2020
- 6Jubileo: An Immersive Simulation Framework for Social Robot Design18 citations · 2023
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