20 citations · 52 across the 14 of their papers we have counts for
5 papers · 1 filter
QuaRL: Quantization for Fast and Environmentally Sustainable Reinforcement Learning
Srivatsan Krishnan, Maximilian Lam, Sharad Chitlangia +4
Deep reinforcement learning continues to show tremendous potential in achieving task-level autonomy, however, its computational and energy demands remain prohibitively high. In thi…
Learning to Seek: Autonomous Source Seeking with Deep Reinforcement Learning Onboard a Nano Drone Microcontroller
Bardienus P. Duisterhof, Srivatsan Krishnan, Jonathan J. Cruz +5
We present fully autonomous source seeking onboard a highly constrained nano quadcopter, by contributing application-specific system and observation feature design to enable infere…
The Role of Compute in Autonomous Aerial Vehicles
Behzad Boroujerdian, Hasan Genc, Srivatsan Krishnan +7
Autonomous-mobile cyber-physical machines are part of our future. Specifically, unmanned-aerial-vehicles have seen a resurgence in activity with use-cases such as package delivery.…
Air Learning: A Deep Reinforcement Learning Gym for Autonomous Aerial Robot Visual Navigation
Srivatsan Krishnan, Behzad Boroujerdian, William Fu +2
We introduce Air Learning, an open-source simulator, and a gym environment for deep reinforcement learning research on resource-constrained aerial robots. Equipped with domain rand…
MAVBench: Micro Aerial Vehicle Benchmarking
Behzad Boroujerdian, Hasan Genc, Srivatsan Krishnan +3
Unmanned Aerial Vehicles (UAVs) are getting closer to becoming ubiquitous in everyday life. Among them, Micro Aerial Vehicles (MAVs) have seen an outburst of attention recently, sp…