Dhaval Gandhi

University of Trento

Papers

1

Total Citations

14

H-Index

1

About

Dhaval Gandhi’s research lies at the intersection of robotics, human-robot interaction, and motion planning, with a particular focus on enabling robots to navigate safely and naturally in human-populated environments. His most-cited work, “Behavioural templates improve robot motion planning with social force model in human environments” (2013, 14 citations), introduces a novel approach that integrates behavioural templates into the Social Force Model (SFM). By embedding the SFM—a well-established framework for modeling pedestrian dynamics—directly into a motion planning algorithm, Gandhi demonstrated how to account for both deterministic and stochastic elements of human behaviour. This work provides a computationally efficient method for robots to anticipate and adapt to human movements, significantly improving their ability to operate in crowded, unpredictable spaces. Though early in his career, Gandhi’s contributions are foundational for researchers developing socially-aware navigation systems, offering a practical template for blending human behavioural models with robotic control. His work underscores the importance of accurate human behaviour modeling in achieving seamless human-robot coexistence.

Research Focus

Key Achievements

1
H-Index
1
Papers
14
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Behavioural templates improve robot motion planning with social force model in human environments
14 citations · 2013
📈 Most Prolific Year: 2013 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Trento

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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