[1] BISCHOFF
R, HUGGENBERGER U, PRASSLER E. KUKA
youBot—a mobile manipulator for research and
education.
Proceedings of
the 2011 IEEE International Conference on Robotics
and
Automation, 2011, May 9 - 13, Shanghai, China.
Piscataway,
NJ, USA: IEEE, 2011: 1 -4.
[2] RAJA R,
DUTTA A, DASGUPTA B. Learning framework for
inverse
kinematics of a highly redundant mobile manipulator.
Robotics and
Autonomous Systems, 2019, 120: Article 103245.
[3] MA'ARIF A,
RAHMANIAR W, VERA M A M, et al. Artificial
potential
field algorithm for obstacle avoidance in UAV quadrotor
for dynamic
environment. Proceedings of the 2021 IEEE
International
Conference on Communication, Networks and
Satellite (
COMNETSAT'21), 2021, Jul 17 - 18, Purwokerto,
Indonesia.
Piscataway, NJ, USA: IEEE, 2021: 184 -189.
[4] ZENG N Y,
ZHANG H, CHEN Y P, et al. Path planning for
intelligent
robot based on switching local evolutionary PSO
algorithm.
Assembly Automation, 2016, 36(2): 120 -126.
[5] CHAKRAVORTY
S, JUNKINS J L. A methodology for intelligent
path planning.
Proceedings of the 2005 IEEE International
Symposium on,
Mediterrean Conference on Control and Automation
Intelligent
Control, 2005, Jun 27 - 29, Limassol, Cyprus.
Piscataway,
NJ, USA: IEEE, 2005: 592 -597.
[6] GREFENSTETTE
J J. Optimization of control parameters for
genetic
algorithms. IEEE Transactions on Systems, Man, and
Cybernetics,
1986, 16(1): 122 -128.
[7] BRAND M,
MASUDA M, WEHNER N, et al. Ant colony
optimization
algorithm for robot path planning. Proceedings of the
2010
International Conference on Computer Design and
Applications:
Vol 3, 2010, Jun 25 - 27, Qinhuangdao, China.
Piscataway,
NJ, USA: IEEE, 2010: 436 -440.
[8] ZHANG D H,
CHEN Y M, HUANG C, et al. Study of path
planning algorithm
based on fuzzy logic. Proceedings of the 2015
International
Conference on Logistics Engineering, Management
and Computer
Science ( LEMCS'15 ), 2015, Jul 29 - 31,
Shenyang,
China. Paris, France: Atlantis Press, 2015: 122 -
126.
[9] KAVRAKI L
E, ŠVESTKA P, LATOMBE J C,
et al.
Probabilistic
roadmaps for path planning in high-dimensional
configuration
spaces. IEEE Transactions on Robotics and
Automation,
1996, 12(4): 566 -580.
[10] WEI K,
REN B Y. A method on dynamic path planning for robotic
manipulator
autonomous obstacle avoidance based on an improved
RRT algorithm.
Sensors, 2018, 18(2): Article 571.
[11] REN J,
MCISAAC K A, PATEL R V. Modified Newton's method
applied to
potential field-based navigation for mobile robots. IEEE
Transactions
on Robotics, 2006, 22(2): 384 -391.
[12] LIU J H,
YANG J G, LIU H P, et al. An improved ant colony
algorithm for
robot path planning. Soft Computing, 2017,
21(19): 5829
-5839.
[13] RAVANKAR
A A, RAVANKAR A, EMARU T, et al. HPPRM:
Hybrid
potential based probabilistic roadmap algorithm for
improved
dynamic path planning of mobile robots. IEEE Access,
2020, 8:
221743 -221766.
[14] HUANG Q,
TANIE K Z, SUGANO S. Coordinated motion
planning for a
mobile manipulator considering stability and
manipulation.
The International Journal of Robotics Research,
2000, 19(8):
732 -742.
[15] LI J L,
XIAO J. A general formulation and approach to
constrained,
continuum manipulation. Advanced Robotics, 2015,
29(13): 889
-899.
[16]
PAPADOPOULOS E, PAPADIMITRIOU I, POULAKAKIS I.
Polynomial-based
obstacle avoidance techniques for nonholonomic
mobile
manipulator systems. Robotics and Autonomous Systems,
2005, 51(4):
229 -247.
[17] PILANIA
V, GUPTA K. A hierarchical and adaptive mobile
manipulator
planner. Proceedings of the 2014 IEEE-RAS
International
Conference on Humanoid Robots, 2014, Nov 18 -
20, Madrid,
Spain. Piscataway, NJ, USA: IEEE, 2014: 45 -
51.
[18] LI Q H,
MU Y Q, YOU Y, et al. A hierarchical motion planning
for mobile
manipulator. IEEJ Transactions on Electrical and
Electronic Engineering,
2020, 15(9): 1390 -1399.
[19] HARGAS Y,
MOKRANE A, HENTOUT A, et al. Mobile
manipulator
path planning based on artificial potential field:
Application on
RobuTER/ ULM. Proceedings of the 4th
International
Conference on Electrical Engineering ( ICEE'15),
2015, Dec 13
-15, Boumerdes, Algeria. Piscataway, NJ, USA:
IEEE, 2015: 1
-6.
[20] CHENG F
Y, JI W, ZHAO D, et al. Apple picking robot obstacle
avoidance
based on the improved artificial potential field method.
Proceedings of
the 5th International Conference on Advanced
Computational
Intelligence ( ICACI'12), 2012, Oct 18 - 20,
Nanjing,
China. Piscataway, NJ, USA: IEEE, 2012: 909 -913.
[21] CAO B, BI
S S , ZHENG J X, et al. Obstacle avoidance algorithm
for redundant
manipulator of improved artificial potential field
method.
Journal of Harbin Institute of Technology,2019, 51(7):
184 -191 (in
Chinese).
[22] WANG H,
SUN Z, LI D Z, et al. An improved RRT based 3-D
path planning
algorithm for UAV. Proceedings of the 2019 Chinese
control and
decision conference (CCDC'19), 2019, Jun 3 - 5,
Nanchang,
China. Piscataway, NJ, USA: IEEE, 2019: 5514 -
5519.
[23]
ABDULKADER M M S, GAJPAL Y, ELMEKKAWY T Y.
Hybridized ant
colony algorithm for the multi compartment vehicle
routing
problem. Applied Soft Computing, 2015, 37: 196 -203.
[24] JIAO Z Q,
MA K, RONG Y L, et al. A path planning method
using adaptive
polymorphic ant colony algorithm for smart
wheelchairs.
Journal of Computational Science, 2018, 25: 50 -
57.
[25] CHEN X,
KONG Y Y, FANG X, et al. A fast two-stage ACO
algorithm for
robotic path planning. Neural Computing and
Applications,
2013, 22(2): 313 -319.
[26] KAVRAKI L
E, ŠVESTKA P, LATOMBE J C,
et al. Probabilistic
roadmaps for
path planning in high-dimensional configuration
spaces. IEEE
Transactions on Robotics and Automation 1996,
12(4): 566
-580.
[27] HSU D,
LATOMBE J C, KURNIAWATI H. On the probabilistic
foundations of
probabilistic roadmap planning. Robotics Research:
Results of the
12th International Symposium ISRR (Springer Tracts
in Advanced
Robotics). Berlin, Germany: Springer, 2007: 83 -
97.
[28] BOHLIN R,
KAVRAKI L E. Path planning using lazy PRM.
Proceedings of
the 2000 IEEE International Conference on Robotics
and Automation
(ICRA'00): Vol 1, 2000, Apr 24 - 28, San
Francisco, CA,
USA. Piscataway, NJ, USA: IEEE, 2000:
521 -528.
[29] LIN Y T.
The Gaussian PRM sampling for dynamic configuration
spaces.
Proceedings of the 9th International Conference on
Control,
Automation, Robotics and Vision, 2006, Dec 5 - 8,
Singapore.
Piscataway, NJ, USA: IEEE, 2006: 1 -5.
[30] BAYAZIT O
B, SONG G, AMATO N M. Ligand binding with
OBPRM and user
input. Proceedings of the 2001 IEEE
International
Conference on Robotics and Automation (ICRA'01):
Vol 1, 2001,
May 21 - 26, Seoul, Republic of Korea.
Piscataway,
NJ, USA: IEEE, 2001: 954 -959.
[31] HSU D,
JIANG T T, REIF J, et al. The bridge test for sampling
narrow
passages with probabilistic roadmap planners. Proceedings
of the 2003
IEEE International Conference on Robotics and
Automation (
ICRA'03): Vol 3, 2003, Sept 14 - 19, Taipei,
China.
Piscataway, NJ, USA: IEEE, 2003: 4420 -4426.
[32] ZHONG J
D, SU J B. Path planning of robot narrow passage based
on
probabilistic landmarks. Control and Decision, 2010, 25(12):
1831 -1836 (in
Chinese).
[33] CHEN G,
JIA Q X, LI T, et al. Recursive calibrations for robot
kinematics
parameters. Journal of Beijing University of Posts and
Telecommunications,
2013, 36(2): 28 -32 (in Chinese).
[34] DENAVIT
J, HARTENBERG R S. A kinematic notation for lower-
pair
mechanisms based on matrices. Journal of Applied
Mechanics,
1955, 22(2): 215 -221.
[35] HAYATI S
A. Robot arm geometric link parameter estimation.
Proceedings of
the 22nd IEEE Conference on Decision and
Control, 1983,
Dec 14 - 16, San Antonio, TX, USA.
Piscataway, NJ,
USA: IEEE, 1983: 1477 -1483.
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