Bertrand Douillard — accepted AI-conference papers

2022

MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction

Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava, Khaled S. Refaat, Nigamaa Nayakanti, Andre Cornman +5

ICRA 2022poster

Predicting the future behavior of road users is one of the most challenging and important problems in autonomous driving. Applying deep learning to this problem requires fusing heterogeneous world state in the form of rich perception signals and map information, and inferring highly multi-modal dist…

Cited by 366 Source ↗Scholar ↗

2022

Narrowing the coordinate-frame gap in behavior prediction models: Distillation for efficient and accurate scene-centric motion forecasting

DiJia Andy Su, Bertrand Douillard, Rami Al-Rfou, Cheol Park, Benjamin Sapp

ICRA 2022poster

Behavior prediction models have proliferated in recent years, especially in the popular real-world robotics application of autonomous driving, where representing the distribution over possible futures of moving agents is essential for safe and comfortable motion planning. In these models, the choice…

Cited by 13 Source ↗Scholar ↗

2015

Supervised Remote Robot with Guided Autonomy and Teleoperation (SURROGATE): A framework for whole-body manipulation

Paul Hebert, Jeremy Ma, James Borders, Alper Aydemir, Max Bajracharya, Nicolas Hudson +4

ICRA 2015poster

The use of the cognitive capabilties of humans to help guide the autonomy of robotics platforms in what is typically called “supervised-autonomy” is becoming more commonplace in robotics research. The work discussed in this paper presents an approach to a human-in-the-loop mode of robot operation th…

Cited by 29 Source ↗Scholar ↗