48 citations · 192 across the 38 of their papers we have counts for
12 papers · 1 filter
Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding
Ruipeng Zhang, Chenning Yu, Jingkai Chen +2
Learning-based methods have shown promising performance for accelerating motion planning, but mostly in the setting of static environments. For the more challenging problem of plan…
Density Planner: Minimizing Collision Risk in Motion Planning with Dynamic Obstacles using Density-based Reachability
Laura Lützow, Yue Meng, Andres Chavez Armijos +1
Uncertainty is prevalent in robotics. Due to measurement noise and complex dynamics, we cannot estimate the exact system and environment state. Since conservative motion planners a…
Barrier functions enable safety-conscious force-feedback control
Charles Dawson, Austin Garrett, Falk Pollok +2
In order to be effective partners for humans, robots must become increasingly comfortable with making contact with their environment. Unfortunately, it is hard for robots to distin…
Case Studies for Computing Density of Reachable States for Safe Autonomous Motion Planning
Yue Meng, Zeng Qiu, Md Tawhid Bin Waez +1
Density of the reachable states can help understand the risk of safety-critical systems, especially in situations when worst-case reachability is too conservative. Recent work prov…
Enforcing safety for vision-based controllers via Control Barrier Functions and Neural Radiance Fields
Mukun Tong, Charles Dawson, Chuchu Fan
To navigate complex environments, robots must increasingly use high-dimensional visual feedback (e.g. images) for control. However, relying on high-dimensional image data to make c…
Certifiable Robot Design Optimization using Differentiable Programming
Charles Dawson, Chuchu Fan
There is a growing need for computational tools to automatically design and verify autonomous systems, especially complex robotic systems involving perception, planning, control, a…
Cooperative Task and Motion Planning for Multi-Arm Assembly Systems
Jingkai Chen, Jiaoyang Li, Yijiang Huang +7
Multi-robot assembly systems are becoming increasingly appealing in manufacturing due to their ability to automatically, flexibly, and quickly construct desired structural designs.…
Robust Counterexample-guided Optimization for Planning from Differentiable Temporal Logic
Charles Dawson, Chuchu Fan
Signal temporal logic (STL) provides a powerful, flexible framework for specifying complex autonomy tasks; however, existing methods for planning based on STL specifications have d…
Safe Control with Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction methods
Charles Dawson, Sicun Gao, Chuchu Fan
Learning-enabled control systems have demonstrated impressive empirical performance on challenging control problems in robotics, but this performance comes at the cost of reduced t…
Multi-agent Motion Planning from Signal Temporal Logic Specifications
Dawei Sun, Jingkai Chen, Sayan Mitra +1
We tackle the challenging problem of multi-agent cooperative motion planning for complex tasks described using signal temporal logic (STL), where robots can have nonlinear and nonh…
SABLAS: Learning Safe Control for Black-box Dynamical Systems
Zengyi Qin, Dawei Sun, Chuchu Fan
Control certificates based on barrier functions have been a powerful tool to generate probably safe control policies for dynamical systems. However, existing methods based on barri…
Learning Safe, Generalizable Perception-based Hybrid Control with Certificates
Charles Dawson, Bethany Lowenkamp, Dylan Goff +1
Many robotic tasks require high-dimensional sensors such as cameras and Lidar to navigate complex environments, but developing certifiably safe feedback controllers around these se…