Papers
8
Total Citations
74
H-Index
5
About
Bruno Leme is a robotics researcher whose work spans agricultural robotics, assistive technology, and robot perception. His most impactful contribution is the development of the MARS-PhenoBot and customized BerryNet system for in-field blueberry fruit phenotyping, which has already garnered 25 citations since 2025. This work addresses the critical need for automated crop monitoring and yield estimation in precision agriculture. Leme has also made significant contributions to assistive robotics, particularly in gait training for older adults. His 2017 paper on a mobile humanoid robot as a walking trainer (15 citations) introduced a novel approach to monitoring and encouraging walking in elderly populations. He further advanced this area with a socially assistive mobile platform for weight-support during gait training (8 citations) and a virtual landmark-based docking control system for assistive mobility devices like wheelchairs (8 citations). In perception, Leme developed techniques for learning depth completion of transparent objects using augmented unpaired data (8 citations) and a force map approach for predicting contact force distribution from vision (5 citations). His work demonstrates a consistent focus on creating intelligent robotic systems that interact safely and effectively with humans and complex environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Gait measurement by a mobile humanoid robot as a walking trainer15 citations · 2017
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- 5A Socially Assistive Mobile Platform for Weight-Support in Gait Training8 citations · 2019
- 6Force Map: Learning to Predict Contact Force Distribution from Vision5 citations · 2023
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