Elastic Strips: A Framework for Motion Generation in Human Environments

By Oliver Brock, Oussama Khatib. Int. J. Robotics Res., 2002

412 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/b740fec2db9066f8faab08aedfec4a1b55837d6b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

In Computer Vision and Pattern Recognition

In Control and Systems Engineering

Citations in the corpus

Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimization (2013, methodology): “Brock and Khatib [4] improved on this idea, enabling trajectory optimization on paths of a robot in 3D, by using the Jacobian to map distances from task space into conﬁguration space.”
Generating Legible Motion (2013, background): “IV), echoing earlier works in motion planning [9, 21, 22, 27, 29, 33, 35], now with legibility as an optimization criterion.”
Human-robot collaborative manipulation planning using early prediction of human motion (2013, background): “In the closely-related topic of robot navigation in the presence of humans, early works were inspired by the social behavior demonstrated by humans [9].”
Robot Collisions: A Survey on Detection, Isolation, and Identification (2017, methodology): “, using artificial potentials [15], [16], elastic strips [17], or other similar variants [18]–[20].”
CHOMP: Covariant Hamiltonian optimization for motion planning (2013, methodology): “Quinlan and Khatib [61] further extended numerical methods in motion replanning by modeling the trajectory as a mass-spring system, an elastic band , and performing replanning by scanning back and forth along the elastic, while moving one mass particle at a time.”
Motion planning with sequential convex optimization and convex collision checking (2014, methodology): “Brock and Khatib [3] improved on this idea, enabling trajectory optimization for a robot in 3D, by using the Jacobian to map distances from task space into conﬁguration space.”
An atlas of physical human-robot interaction (2008, neutral): “One example is the elastic strip framework [37], where the local modiﬁcation of motion is performed in a task-consistent manner, leaving primary (Cartesian) task execution possibly unaﬀected by obstacle avoidance.”
CHOMP: Gradient optimization techniques for efficient motion planning (2009, methodology): “Gradient based methods are used to find a minimum-energy path [20], [4].”
Real-Time Perception Meets Reactive Motion Generation (2017, background): “Oneexample is the elastic-strip framework [20] which combines localcontrolwithmotionplanning.”
Spatial adaption of robot trajectories based on laplacian trajectory editing (2015, methodology): “3.3 shares common properties with the elastic strips framework (Brock and Khatib 2002).”
Human-aware robot navigation: A survey (2013, background): “Local Planning [2, 8, 11, 19, 30, 34, 39, 43, 44, 45, 48, 49, 51, 54, 57, 62, 76, 83, 84, 87, 89, 90, 91, 99, 104, 105, 26] 27 Behavior Selection [1, 17, 19, 27, 30, 33, 34, 35, 43, 56, 79, 69, 70, 81] 14 Global Planning [6, 7, 21, 28, 30, 37, 38, 43, 44, 48, 49, 50, 54, 56, 57, 59, 60, 62, 65, 69, ”