https://deepai.org/publication/mesh-manifold-based-riemannian-motion-planning-for-omnidirectional-micro-aerial-vehicles
02/20/21 - This paper presents a novel on-line path planning method that enables aerial robots to interact with surfaces. We present a soluti...
motion planningmeshmanifoldbasedriemannian
https://slides.com/russtedrake/fall23-lec11
MIT Robotic Manipulation Fall 2023 http://manipulation.csail.mit.edu
motion planninglecture
https://deepai.org/publication/density-planner-minimizing-collision-risk-in-motion-planning-with-dynamic-obstacles-using-density-based-reachability
10/05/22 - Autonomous systems with uncertainties are prevalent in robotics. However, ensuring the safety of those systems is challenging due ...
in motiondensityplannerminimizingcollision
https://deepai.org/publication/streamlines-for-motion-planning-in-underwater-currents
01/28/19 - Motion planning for underwater vehicles must consider the effect of ocean currents. We present an efficient method to compute reac...
motion planningstreamlinesunderwatercurrents
https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2023.1255696/full
In control theory, reactive methods have been widely celebrated owing to their success in providing robust, provably convergent solutions to control problems...
motion planningfrontiersreactiveoptimalclass
https://www.mdpi.com/1424-8220/24/23/7652
Humanoid robots are typically designed for static environments, but real-world applications demand robust performance under dynamic, uncertain conditions. This...
motion planninghumanoid robotcontrolenvironmental
https://www.bosch.com/stories/finding-the-best-way-to-go-bench-mr-a-benchmark-for-robot-motion-algorithms/
Bosch Research developed "Bench-MR" - a benchmarking framework for sampling-based algorithms in the field of robot motion planning. The project was a joint...
robot motion planningboschresearchglobal