Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Andreas Orthey"'
Autor:
Constantinos Chamzas, Carlos Quintero-Pena, Zachary Kingston, Andreas Orthey, Daniel Rakita, Michael Gleicher, Marc Toussaint, Lydia E. Kavraki
Publikováno v:
IEEE Robotics and Automation Letters. 7:882-889
Recently, there has been a wealth of development in motion planning for robotic manipulation new motion planners are continuously proposed, each with their own unique strengths and weaknesses. However, evaluating new planners is challenging and resea
Autor:
Marc Toussaint, Andreas Orthey
Publikováno v:
IEEE Transactions on Robotics. 37:1891-1905
Sampling-based planning methods often become inefficient due to narrow passages. Narrow passages induce a higher runtime, because the chance to sample them becomes vanishingly small. In recent work, we showed that narrow passages can be approached by
Robots often need to solve path planning problems where essential and discrete aspects of the environment are partially observable. This introduces a multi-modality, where the robot must be able to observe and infer the state of its environment. To t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2e15274d076be252c2510941ce516fd
http://arxiv.org/abs/2204.04444
http://arxiv.org/abs/2204.04444
Optimal sampling based motion planning and trajectory optimization are two competing frameworks to generate optimal motion plans. Both frameworks have complementary properties: Sampling based planners are typically slow to converge, but provide optim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7cb5ce0db49499843b55f25ea648c5e3
We present a motion planner for planning through space-time with dynamic obstacles, velocity constraints, and unknown arrival time. Our algorithm, Space-Time RRT* (ST-RRT*), is a probabilistically complete, bidirectional motion planning algorithm, wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1c6c1ec6febbde3b273438171e6cfe7
Autor:
Andreas Orthey, Marc Toussaint
Publikováno v:
Springer Proceedings in Advanced Robotics ISBN: 9783030954581
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c392390437b97099d7812751c1f5c2c
https://doi.org/10.1007/978-3-030-95459-8_4
https://doi.org/10.1007/978-3-030-95459-8_4
Autor:
Marc Toussaint, Andreas Orthey
Publikováno v:
2021 IEEE International Conference on Robotics and Automation (ICRA 2021)
ICRA
ICRA
Sparse roadmaps are important to compactly represent state spaces, to determine problems to be infeasible and to terminate in finite time. However, sparse roadmaps do not scale well to high-dimensional planning problems. In prior work, we showed impr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9af9d23a5c7203f75b048f6407224c8b
https://hdl.handle.net/21.11116/0000-000A-DCB3-4
https://hdl.handle.net/21.11116/0000-000A-DCB3-4
Autor:
Marc Toussaint, Andreas Orthey
Publikováno v:
Algorithmic Foundations of Robotics XIV ISBN: 9783030667221
WAFR
WAFR
Multi-robot motion planning problems often have many local minima. It is essential to visualize those local minima such that we can better understand, debug and interact with multi-robot systems. Towards this goal, we present the multi-robot motion e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31bcea229f6df4a381113b5bc7e596bd
https://doi.org/10.1007/978-3-030-66723-8_30
https://doi.org/10.1007/978-3-030-66723-8_30
Publikováno v:
IEEE Transactions on Robotics
Robotic assembly planning enables architects to explicitly account for the assembly process during the design phase, and enables efficient building methods that profit from the robots' different capabilities. Previous work has addressed planning of r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f2198221894066bd65332303178b4d2
Publikováno v:
2021 IEEE 17th International Conference on Automation Science and Engineering (CASE 2021)
CASE
CASE
Contact-based motion planning for manipulation, object exploration or balancing often requires finding sequences of fixed and sliding contacts and planning the transition from one contact in the environment to another. However, most existing algorith
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2bf3604ddaa7513d8e16d66824adf8d8