PMID- 34447789
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20210827
IS  - 2296-9144 (Electronic)
IS  - 2296-9144 (Linking)
VI  - 8
DP  - 2021
TI  - NSPG: An Efficient Posture Generator Based on Null-Space Alteration and 
      Kinetostatics Constraints.
PG  - 715325
LID - 10.3389/frobt.2021.715325 [doi]
LID - 715325
AB  - Most of the locomotion and contact planners for multi-limbed robots rely on a 
      reduction of the search space to improve the performance of their algorithm. 
      Posture generation plays a fundamental role in these types of planners providing 
      a collision-free, statically stable whole-body posture, projected onto the 
      planned contacts. However, posture generation becomes particularly tedious for 
      complex robots moving in cluttered environments, in which feasibility can be hard 
      to accomplish. In this work, we take advantage of the kinematic structure of a 
      multi-limbed robot to present a posture generator based on hierarchical inverse 
      kinematics and contact force optimization, called the null-space posture 
      generator (NSPG), able to efficiently satisfy the aforementioned requisites in 
      short times. A new configuration of the robot is produced through conservatively 
      altering a given nominal posture exploiting the null-space of the contact 
      manifold, satisfying geometrical and kinetostatics constraints. This is achieved 
      through an adaptive random velocity vector generator that lets the robot explore 
      its workspace. To prove the validity and generality of the proposed method, 
      simulations in multiple scenarios are reported employing different robots: a 
      wheeled-legged quadruped and a biped. Specifically, it is shown that the NSPG is 
      particularly suited in complex cluttered scenarios, in which linear collision 
      avoidance and stability constraints may be inefficient due to the high 
      computational cost. In particular, we show an improvement of performances being 
      our method able to generate twice feasible configurations in the same period. A 
      comparison with previous methods has been carried out collecting the obtained 
      results which highlight the benefits of the NSPG. Finally, experiments with the 
      CENTAURO platform, developed at Istituto Italiano di Tecnologia, are carried out 
      showing the applicability of the proposed method to a real corridor scenario.
CI  - Copyright (c) 2021 Rossini, Hoffman, Laurenzi and Tsagarakis.
FAU - Rossini, Luca
AU  - Rossini L
AD  - Humanoids and Human Centred Mechatronics Lab, Istituto Italiano di Tecnologia 
      (IIT), Genova, Italy.
AD  - DIBRIS, Universita di Genova, Genova, Italy.
FAU - Hoffman, Enrico Mingo
AU  - Hoffman EM
AD  - Humanoids and Human Centred Mechatronics Lab, Istituto Italiano di Tecnologia 
      (IIT), Genova, Italy.
FAU - Laurenzi, Arturo
AU  - Laurenzi A
AD  - Humanoids and Human Centred Mechatronics Lab, Istituto Italiano di Tecnologia 
      (IIT), Genova, Italy.
FAU - Tsagarakis, Nikos G
AU  - Tsagarakis NG
AD  - Humanoids and Human Centred Mechatronics Lab, Istituto Italiano di Tecnologia 
      (IIT), Genova, Italy.
LA  - eng
PT  - Journal Article
DEP - 20210810
PL  - Switzerland
TA  - Front Robot AI
JT  - Frontiers in robotics and AI
JID - 101749350
PMC - PMC8384489
OTO - NOTNLM
OT  - hierarchical inverse kinematics
OT  - humanoid robot
OT  - legged robot
OT  - optimization
OT  - posture generation
OT  - whole-body planning
COIS- The authors declare that the research was conducted in the absence of any 
      commercial or financial relationships that could be construed as a potential 
      conflict of interest.
EDAT- 2021/08/28 06:00
MHDA- 2021/08/28 06:01
PMCR- 2021/08/10
CRDT- 2021/08/27 06:58
PHST- 2021/05/26 00:00 [received]
PHST- 2021/07/12 00:00 [accepted]
PHST- 2021/08/27 06:58 [entrez]
PHST- 2021/08/28 06:00 [pubmed]
PHST- 2021/08/28 06:01 [medline]
PHST- 2021/08/10 00:00 [pmc-release]
AID - 715325 [pii]
AID - 10.3389/frobt.2021.715325 [doi]
PST - epublish
SO  - Front Robot AI. 2021 Aug 10;8:715325. doi: 10.3389/frobt.2021.715325. eCollection 
      2021.