A Human Aware Mobile Robot Motion Planner

By Emrah Akin Sisbot, Luis Felipe Marin-Urias, Rachid Alami, Thierry Siméon. 2007

534 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering, Social Psychology, Robotics & Control

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Citations in the corpus

Learning Trajectory Preferences for Manipulators via Iterative Improvement (2013, neutral): “[34, 33] and Mainprice et. al.”
Plan explicability and predictability for robot task planning (2015, background): “In prior works, this issue is addressed under human-aware planning [22, 4, 2] in which agents take the human’s activities and intents into account when constructing their plans.”
From Proxemics Theory to Socially-Aware Navigation: A Survey (2014, background): “…Passing people [50,55,73,75] Staying in line [71] Approaching humans [4,15,86,105] Following people [28,69,108] Walking side-by-side [67] Focused and Combination of previous listed tasks [34,87,93] others by means of nonverbal behaviors or by the knowledge of rules in social spaces (Fig.”
Learning preferences for manipulation tasks from online coactive feedback (2015, unknown): “[55, 54] and Mainprice et. al.”
Planning for serendipity (2015, background): “Indeed there has been a lot of work under the umbrella of “human-aware” planning, both in the context of path planning [3], [4] and in task planning [5], [6], that aim to provide social skills to robots so as to make them produce plans conforming to desired behaviors when humans and robots operate i”
Artificial cognition for social human-robot interaction: An implementation (2017, methodology): “We briefly mention our human-aware motion and manipulation planner [91,105,92,97,93,95], and finally present two execution controller, the PRS-based Shary [83,89,2] and the event-driven pyRobots [85].”
Human-aware robot navigation: A survey (2013, background): “The most common approach to avoid discomfort due to small distance is to define areas around humans as cost functions or potential fields [34, 44, 83, 89, 91].”
Core Challenges of Social Robot Navigation: A Survey (2021, background): “[228] describe a series of navigation interactions between a robot running their”
Learning socially normative robot navigation behaviors with Bayesian inverse reinforcement learning (2016, methodology): “Other works using manually designed behavior or not based on IRL, include Sisbot et al. [10] who developed a human-aware motion planner by using Gaussians to model the personal space of individuals.”
A Survey of Methods for Safe Human-Robot Interaction (2017, methodology): “This work, which focuses on close-proximity manipulation, is similar to a prior investigation of co-navigation conducted by the authors (Sisbot et al., 2007).”
Human-robot collaborative manipulation planning using early prediction of human motion (2013, background): “clearance, but also about how visible the robot is along the robot motion to avoid the effect of surprise [10] leading to more legible navigation plans.”
Planning human-aware motions using a sampling-based costmap planner (2011, methodology): “The planners of [ 17 ], [18] were based on a direct search on the resulting cartesian grids to produce legible and comfortable motions using basic graph search techniques.”
Algorithms for collision-free navigation of mobile robots in complex cluttered environments: a survey (2014, unknown): “For avoiding humans, several models of socially acceptable pedestrian behavior are available (see, e.g., [81, 203, 254, 314]).”
Sharing effort in planning human-robot handover tasks (2012, background): “These constraints have been introduced and used in [20] to generate navigation human-aware motions.”
Shared autonomy via hindsight optimization for teleoperation and teaming (2017, background): “For static users, researchers have incorporated collaboration constraints such as safety and social acceptability (Sisbot et al., 2007), and task constraints such as user visibility and reachability (Sisbot et al., 2010; Pandey and Alami, 2010; Mainprice et al., 2011).”