Legibility of robot approach trajectories with minimum jerk path planning

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)


When a robot approaches a person, the chosen trajectory ideally informs the person not only about the robot’s intended target location, but also its intended orientation. However, planning a straight line to the goal location does not guarantee a correct final orientation, potentially causing confusion as the robot eventually rotates towards its unsuspecting target. One method that could remedy this problem is minimum jerk path planning, which results in the smoothest possible path that ends in the pre-specified final orientation. The technique is already widely used in robotic arm motion planning, but existing work is lacking for regular path planning. The aim of the current study is to implement minimum jerk path planning for the Nao robot and to evaluate the potential benefit for human observers to infer the intended target of the robot. Results show that minimum jerk path planning significantly improves people’s recognition of the robot’s destination compared to straight line path planning. Meanwhile, the perceived likeability and human likeness of the robot remain the same, suggesting that implementing smooth robot path planning that includes the final orientation leads to more predictable robot approaching behaviour.

Human-aware navigation Path planning Robot intention Human-robot interaction
Original languageEnglish
Title of host publicationSocial Robotics
Subtitle of host publicationProceedings of the 12th International Conference, ICSR 2020, Golden, CO, USA, November 14–18, 2020
EditorsAlan R. Wagner, David Feil-Seifer, Kerstin S. Haring, Silvia Rossi, Thomas Williams, Hongsheng He, Shuzhi Sam Ge
Number of pages12
ISBN (Print)9783030620554
Publication statusPublished - Nov 2020
Event12th International Conference on Social Robotics, ICSR 2020 - Golden, United States
Duration: 14 Nov 202018 Nov 2020
Conference number: 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12483 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th International Conference on Social Robotics, ICSR 2020
Abbreviated titleICSR 2020
Country/TerritoryUnited States


  • Human-aware navigation
  • Human-robot interaction
  • Path planning
  • Robot intention


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