595 citations · 1.9k across the 91 of their papers we have counts for
19 papers · 1 filter
Don't Run with Scissors: Pruning Breaks VLA Models but They Can Be Recovered
Jason Jabbour, Dong-Ki Kim, Max Smith +6
Vision-Language-Action (VLA) models are a promising paradigm for field robotics, but their deployment is bottlenecked by strict edge SWaP-C constraints. Compression techniques such…
Generative AI in Embodied Systems: System-Level Analysis of Performance, Efficiency and Scalability
Zishen Wan, Jiayi Qian, Yuhang Du +6
Embodied systems, where generative autonomous agents engage with the physical world through integrated perception, cognition, action, and advanced reasoning powered by large langua…
VaPr: Variable-Precision Tensors to Accelerate Robot Motion Planning
Yu-Shun Hsiao, Siva Kumar Sastry Hari, Balakumar Sundaralingam +5
High-dimensional motion generation requires numerical precision for smooth, collision-free solutions. Typically, double-precision or single-precision floating-point (FP) formats ar…
RobotPerf: An Open-Source, Vendor-Agnostic, Benchmarking Suite for Evaluating Robotics Computing System Performance
Víctor Mayoral-Vilches, Jason Jabbour, Yu-Shun Hsiao +16
We introduce RobotPerf, a vendor-agnostic benchmarking suite designed to evaluate robotics computing performance across a diverse range of hardware platforms using ROS 2 as its com…
BERRY: Bit Error Robustness for Energy-Efficient Reinforcement Learning-Based Autonomous Systems
Zishen Wan, Nandhini Chandramoorthy, Karthik Swaminathan +3
Autonomous systems, such as Unmanned Aerial Vehicles (UAVs), are expected to run complex reinforcement learning (RL) models to execute fully autonomous position-navigation-time tas…
Robotic Computing on FPGAs: Current Progress, Research Challenges, and Opportunities
Zishen Wan, Ashwin Lele, Bo Yu +5
Robotic computing has reached a tipping point, with a myriad of robots (e.g., drones, self-driving cars, logistic robots) being widely applied in diverse scenarios. The continuous…
RobotCore: An Open Architecture for Hardware Acceleration in ROS 2
Víctor Mayoral-Vilches, Sabrina M. Neuman, Brian Plancher +1
Hardware acceleration can revolutionize robotics, enabling new applications by speeding up robot response times while remaining power-efficient. However, the diversity of accelerat…
Analyzing and Improving Fault Tolerance of Learning-Based Navigation Systems
Zishen Wan, Aqeel Anwar, Yu-Shun Hsiao +3
Learning-based navigation systems are widely used in autonomous applications, such as robotics, unmanned vehicles and drones. Specialized hardware accelerators have been proposed f…
Roofline Model for UAVs:A Bottleneck Analysis Tool for Designing Compute Systems for Autonomous Drones
Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj +2
We present a bottleneck analysis tool for designing compute systems for autonomous Unmanned Aerial Vehicles (UAV). The tool provides insights by exploiting the fundamental relation…
AutoSoC: Automating Algorithm-SOC Co-design for Aerial Robots
Srivatsan Krishnan, Thierry Tambe, Zishen Wan +1
Aerial autonomous machines (Drones) has a plethora of promising applications and use cases. While the popularity of these autonomous machines continues to grow, there are many chal…
GRiD: GPU-Accelerated Rigid Body Dynamics with Analytical Gradients
Brian Plancher, Sabrina M. Neuman, Radhika Ghosal +2
We introduce GRiD: a GPU-accelerated library for computing rigid body dynamics with analytical gradients. GRiD was designed to accelerate the nonlinear trajectory optimization subp…
RoboRun: A Robot Runtime to Exploit Spatial Heterogeneity
Behzad Boroujerdian, Radhika Ghosal, Jonathan Cruz +2
The limited onboard energy of autonomous mobile robots poses a tremendous challenge for practical deployment. Hence, efficient computing solutions are imperative. A crucial shortco…
Sniffy Bug: A Fully Autonomous Swarm of Gas-Seeking Nano Quadcopters in Cluttered Environments
Bardienus P. Duisterhof, Shushuai Li, Javier Burgués +2
Nano quadcopters are ideal for gas source localization (GSL) as they are safe, agile and inexpensive. However, their extremely restricted sensors and computational resources make G…
MAVFI: An End-to-End Fault Analysis Framework with Anomaly Detection and Recovery for Micro Aerial Vehicles
Yu-Shun Hsiao, Zishen Wan, Tianyu Jia +6
Safety and resilience are critical for autonomous unmanned aerial vehicles (UAVs). We introduce MAVFI, the micro aerial vehicles (MAVs) resilience analysis methodology to assess th…
AutoPilot: Automating SoC Design Space Exploration for SWaP Constrained Autonomous UAVs
Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj +6
Building domain-specific accelerators for autonomous unmanned aerial vehicles (UAVs) is challenging due to a lack of systematic methodology for designing onboard compute. Balancing…
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…