A review on interaction control for contact robots through intent detection
Interaction control presents opportunities for contact robots physically interacting with their
human user, such as assistance targeted to each human user, communication of goals to …
human user, such as assistance targeted to each human user, communication of goals to …
Physical interaction as communication: Learning robot objectives online from human corrections
When a robot performs a task next to a human, physical interaction is inevitable: the human
might push, pull, twist, or guide the robot. The state of the art treats these interactions as …
might push, pull, twist, or guide the robot. The state of the art treats these interactions as …
Unified learning from demonstrations, corrections, and preferences during physical human–robot interaction
Humans can leverage physical interaction to teach robot arms. This physical interaction
takes multiple forms depending on the task, the user, and what the robot has learned so far …
takes multiple forms depending on the task, the user, and what the robot has learned so far …
Spatial iterative learning control for robotic path learning
A spatial iterative learning control (sILC) method is proposed for a robot to learn a desired
path in an unknown environment. When interacting with the environment, the robot initially …
path in an unknown environment. When interacting with the environment, the robot initially …
Corrective shared autonomy for addressing task variability
Many tasks, particularly those involving interaction with the environment, are characterized
by high variability, making robotic autonomy difficult. One flexible solution is to introduce the …
by high variability, making robotic autonomy difficult. One flexible solution is to introduce the …
Haptics based multi-level collaborative steering control for automated driving
Increasing the capability of automated driving vehicles is motivated by environmental,
productivity, and traffic safety benefits. But over-reliance on the automation system is known …
productivity, and traffic safety benefits. But over-reliance on the automation system is known …
An incremental inverse reinforcement learning approach for motion planning with separated path and velocity preferences
Humans often demonstrate diverse behaviors due to their personal preferences, for
instance, related to their individual execution style or personal margin for safety. In this …
instance, related to their individual execution style or personal margin for safety. In this …
Power assist rehabilitation robot and motion intention estimation
ZA Adeola-Bello, NZ Azlan - International Journal of Robotics and …, 2022 - pubs2.ascee.org
This article attempts to review papers on power assist rehabilitation robots, human motion
intention, control laws, and estimation of power assist rehabilitation robots based on human …
intention, control laws, and estimation of power assist rehabilitation robots based on human …
Hybrid trajectory replanning-based dynamic obstacle avoidance for physical human-robot interaction
This paper presents a hierarchical replanning framework that rapidly modulates the ongoing
trajectory to help 7-DoF redundant manipulators avoid dynamic obstacles in physical human …
trajectory to help 7-DoF redundant manipulators avoid dynamic obstacles in physical human …
Spatial iterative learning control with human guidance and visual detection for path learning and tracking
A popular path learning method is to use off-line programming by demonstration (PbD) to
plan a rough path, but it is subjected to uncertainties in the environment so needs to be …
plan a rough path, but it is subjected to uncertainties in the environment so needs to be …