Zobrazeno 1 - 10
of 39
pro vyhledávání: '"PLANCHER, BRIAN"'
The end of Moore's Law and Dennard Scaling has combined with advances in agile hardware design to foster a golden age of domain-specific acceleration. However, this new frontier of computing opportunities is not without pitfalls. As computer architec
Externí odkaz:
http://arxiv.org/abs/2407.17311
Conic constraints appear in many important control applications like legged locomotion, robotic manipulation, and autonomous rocket landing. However, current solvers for conic optimization problems have relatively heavy computational demands in terms
Externí odkaz:
http://arxiv.org/abs/2403.18149
Autor:
Stewart, Matthew, Moss, Emanuel, Warden, Pete, Plancher, Brian, Kennedy, Susan, Sloane, Mona, Reddi, Vijay Janapa
Artificial intelligence systems connected to sensor-laden devices are becoming pervasive, which has significant implications for a range of AI risks, including to privacy, the environment, autonomy, and more. There is therefore a growing need for inc
Externí odkaz:
http://arxiv.org/abs/2402.11183
Model-predictive control (MPC) is a powerful tool for controlling highly dynamic robotic systems subject to complex constraints. However, MPC is computationally demanding, and is often impractical to implement on small, resource-constrained robotic p
Externí odkaz:
http://arxiv.org/abs/2310.16985
Autor:
Grossman, Lev, Plancher, Brian
Perceptive deep reinforcement learning (DRL) has lead to many recent breakthroughs for complex AI systems leveraging image-based input data. Applications of these results range from super-human level video game agents to dexterous, physically intelli
Externí odkaz:
http://arxiv.org/abs/2310.01767
Autor:
Mayoral-Vilches, Víctor, Jabbour, Jason, Hsiao, Yu-Shun, Wan, Zishen, Crespo-Álvarez, Martiño, Stewart, Matthew, Reina-Muñoz, Juan Manuel, Nagras, Prateek, Vikhe, Gaurav, Bakhshalipour, Mohammad, Pinzger, Martin, Rass, Stefan, Panigrahi, Smruti, Corradi, Giulio, Roy, Niladri, Gibbons, Phillip B., Neuman, Sabrina M., Plancher, Brian, Reddi, Vijay Janapa
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 common baseline. The suite encompasses ROS 2 packages covering the full r
Externí odkaz:
http://arxiv.org/abs/2309.09212
Nonlinear Model Predictive Control (NMPC) is a state-of-the-art approach for locomotion and manipulation which leverages trajectory optimization at each control step. While the performance of this approach is computationally bounded, implementations
Externí odkaz:
http://arxiv.org/abs/2309.08079
Autor:
Bu, Xueyi, Plancher, Brian
There has been a growing interest in parallel strategies for solving trajectory optimization problems. One key step in many algorithmic approaches to trajectory optimization is the solution of moderately-large and sparse linear systems. Iterative met
Externí odkaz:
http://arxiv.org/abs/2309.06427
Autor:
Stewart, Matthew, Warden, Pete, Omri, Yasmine, Prakash, Shvetank, Santos, Joao, Hymel, Shawn, Brown, Benjamin, MacArthur, Jim, Jeffries, Nat, Katti, Sachin, Plancher, Brian, Reddi, Vijay Janapa
Machine learning (ML) sensors are enabling intelligence at the edge by empowering end-users with greater control over their data. ML sensors offer a new paradigm for sensing that moves the processing and analysis to the device itself rather than rely
Externí odkaz:
http://arxiv.org/abs/2306.08848
Autor:
Prakash, Shvetank, Stewart, Matthew, Banbury, Colby, Mazumder, Mark, Warden, Pete, Plancher, Brian, Reddi, Vijay Janapa
The sustained growth of carbon emissions and global waste elicits significant sustainability concerns for our environment's future. The growing Internet of Things (IoT) has the potential to exacerbate this issue. However, an emerging area known as Ti
Externí odkaz:
http://arxiv.org/abs/2301.11899