Parting with misconceptions about learning-based vehicle motion planning
The release of nuPlan marks a new era in vehicle motion planning research, offering the first
large-scale real-world dataset and evaluation schemes requiring both precise short-term …
large-scale real-world dataset and evaluation schemes requiring both precise short-term …
Open-sourced data ecosystem in autonomous driving: the present and future
With the continuous maturation and application of autonomous driving technology, a
systematic examination of open-source autonomous driving datasets becomes instrumental …
systematic examination of open-source autonomous driving datasets becomes instrumental …
Towards learning-based planning: The nuPlan benchmark for real-world autonomous driving
N Karnchanachari, D Geromichalos, KS Tan… - arXiv preprint arXiv …, 2024 - arxiv.org
Machine Learning (ML) has replaced traditional handcrafted methods for perception and
prediction in autonomous vehicles. Yet for the equally important planning task, the adoption …
prediction in autonomous vehicles. Yet for the equally important planning task, the adoption …
Dtpp: Differentiable joint conditional prediction and cost evaluation for tree policy planning in autonomous driving
Motion prediction and cost evaluation are vital components in the decision-making system of
autonomous vehicles. However, existing methods often ignore the importance of cost …
autonomous vehicles. However, existing methods often ignore the importance of cost …
Differentiable constrained imitation learning for robot motion planning and control
Motion planning and control are crucial components of robotics applications like automated
driving. Here, spatio-temporal hard constraints like system dynamics and safety boundaries …
driving. Here, spatio-temporal hard constraints like system dynamics and safety boundaries …
Bounded Low Latency via Inverse Reinforcement Learning
Accurate traffic prediction is essential for effective resource utilization and improving user
experience quality in next generation wireless networks. Machine Learning (ML) techniques …
experience quality in next generation wireless networks. Machine Learning (ML) techniques …
CoBL-Diffusion: Diffusion-Based Conditional Robot Planning in Dynamic Environments Using Control Barrier and Lyapunov Functions
Equipping autonomous robots with the ability to navigate safely and efficiently around
humans is a crucial step toward achieving trusted robot autonomy. However, generating …
humans is a crucial step toward achieving trusted robot autonomy. However, generating …
ReMAV: Reward Modeling of Autonomous Vehicles for Finding Likely Failure Events
Autonomous vehicles are advanced driving systems that are well known for being
vulnerable to various adversarial attacks, compromising the vehicle's safety, and posing …
vulnerable to various adversarial attacks, compromising the vehicle's safety, and posing …
Trajectory Planning for Autonomous Vehicle Using Iterative Reward Prediction in Reinforcement Learning
H Park - arXiv preprint arXiv:2404.12079, 2024 - arxiv.org
Traditional trajectory planning methods for autonomous vehicles have several limitations.
Heuristic and explicit simple rules make trajectory lack generality and complex motion. One …
Heuristic and explicit simple rules make trajectory lack generality and complex motion. One …