Maxwell Forbes
Papers
5
Total Citations
123
H-Index
4
About
Maxwell Forbes is a leading researcher in human-robot interaction, with a primary focus on making robot programming accessible to non-experts. His work centers on Programming by Demonstration (PbD), where users teach robots new behaviors through natural demonstrations rather than traditional coding. Forbes’s key contribution lies in integrating situated spatial language understanding with PbD, allowing users to augment physical demonstrations with intuitive speech commands—a natural, hands-free way to guide robot learning. His most cited paper (65 citations) pioneered this approach, enabling robots to interpret spatial language in context. To overcome the bottleneck of requiring numerous expensive human demonstrations, Forbes innovatively introduced crowdsourcing into imitation learning, showing how distributed online workers can provide action fixes and supplementary demonstrations (26 and 25 citations respectively). This work dramatically accelerates robot learning while reducing the burden on individual users. His research on balancing shared autonomy with human-robot communication (3 citations) further explores efficient human-robot collaboration. Forbes’s contributions are foundational to democratizing robot programming, making it possible for everyday users to teach robots complex tasks without specialized technical knowledge—a critical step toward widespread robot adoption in homes and workplaces.
Research Focus
Key Achievements
Top Papers
- 1
- 2Accelerating imitation learning through crowdsourcing26 citations · 2014
- 3Robot Programming by Demonstration with Crowdsourced Action Fixes25 citations · 2014
- 4Programming by Demonstration with Situated Semantic Parsing4 citations · 2014
- 5Balancing Shared Autonomy with Human-Robot Communication3 citations · 2018