Papers
14
Total Citations
154
H-Index
7
About
Jorge Batista is a robotics and computer vision researcher whose work spans several decades of innovation in autonomous systems, visual control, and medical robotics. Best known for his foundational contributions to visual pursuit and active vision systems, Batista explored how mobile robots equipped with artificial vision can track and follow moving objects in real time — research that earned his 1998 paper on machine pursuit experiments over 63 citations, making it his most influential work. His early career also addressed critical challenges in camera calibration and multi-sensor integration, with his 1993 monoplanar calibration method offering a practical linear approach that advanced robotic perception. Throughout the 2000s, Batista developed sophisticated binocular active vision architectures capable of real-time visual behaviors, including optical flow-based pursuit and gaze stabilization. More recently, his research has expanded into soft robotics and biomedical applications, including ultrasound-tracked magnetically actuated soft robots for minimally invasive procedures, and human-robot interaction studies exploring following robots for gait assessment. Across more than three decades, Batista's interdisciplinary contributions demonstrate a sustained commitment to bridging theoretical computer vision with practical robotic systems, leaving a meaningful mark on both autonomous navigation and emerging medical robotics.
Research Focus
Key Achievements
Top Papers
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- 4A distributed system for robotic multi-sensor integration10 citations · 1990
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- 6Real-time visual behaviors with a binocular active vision system8 citations · 2002
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- 8Monoplanar Camera Calibration Iterative Multi-Step Approach7 citations · 1993
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- 10Pursuit control in a binocular active vision system using optical flow4 citations · 1996