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Strategy of Motion Planning of Soft Robot Based on Linear Interpolation of Cubic Polynomial

Abhishek Shrivastava, Mukesh Kumar Nag, Saksham Bajpai

Abstract


Soft robots frequently take design cues from organic mechanisms that operate electrically or with natural fibres. Soft robots have several advantages over traditional robots, including the ability to adapt to wearable technologies, secure human-machine contact, a simple gripping mechanism, and more. Because of their distinct characteristics and advantages, soft robots have a wide range of applications. This study investigates the motion planning of a bionic robot using linear interpolation of a cubic polynomial. The temporal fluctuation of the polynomial profile as influenced by position, speed, and acceleration is depicted. The position profile appears smooth, but the velocity and acceleration profile exhibits even oscillations as a result of the constant change in joint velocity, as discovered. As a result, with this approach, the end-effector of a flexible robot can achieve the desired pose with minimal trajectory deviation.


Keywords


Soft robot, Motion planning, polynomial profile, joint parameters, human-machine interactions

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References


Iida F, Ijspeert AJ. Biologically inspired robotics. Springer Handbook of Robotics. 2016:2015-34.

Jaeger HM. Celebrating soft matter’s 10th anniversary: Toward jamming by design. Soft matter. 2015;11(1):12-27.

Alam Z, Dalla VK, Shrivastava A. Finite element analysis of fundamental deformation of robot soft finger. InAIP Conference Proceedings 2021 May 13 (Vol. 2341, No. 1, p. 020039). AIP Publishing LLC.

Dautenhahn K, Nehaniv CL, Walters ML, et al. KASPAR–a minimally expressive humanoid robot for human–robot interaction research. Applied Bionics and Biomechanics. 2009 Jan 1;6(3-4):369-97.

Navarro X, Krueger TB, Lago N, et al. A critical review of interfaces with the peripheral nervous system for the control of neuroprostheses and hybrid bionic systems. Journal of the Peripheral Nervous System. 2005 Sep;10(3):229-58.

Shrivastava A, Dalla VK. Failure control and energy optimization of multi-axes space manipulator through genetic algorithm approach. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 2021 Oct;43:1-7.

Shrivastava A, Dalla VK. Strategy of smooth motion planning of multi-axes space manipulator avoiding dynamic singularity in Cartesian space. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 2022 Jul;44(7):1-20.

Righetti L, Kalakrishnan M, Pastor P, et al. An autonomous manipulation system based on force control and optimization. Autonomous Robots. 2014 Jan;36:11-30.

Shrivastava A, Dalla VK. Jerk Optimized Motion Planning of Redundant Space Robot Based on Grey-Wolf Optimization Approach. Arabian Journal for Science and Engineering. 2022 Jun 14:1-3.

Lampariello R, Nguyen-Tuong D, et al. Trajectory planning for optimal robot catching in real-time. In2011 IEEE International Conference on Robotics and Automation 2011 May 9 (pp. 3719-3726). IEEE.

Sundaralingam B, Hermans T. Relaxed-rigidity constraints: kinematic trajectory optimization and collision avoidance for in-grasp manipulation. Autonomous Robots. 2019 Feb 15;43:469-83.

Dubowsky S, Papadopoulos E. The kinematics, dynamics, and control of free-flying and free-floating space robotic systems. IEEE Transactions on robotics and automation. 1993 Oct;9(5):531-43.

Huang J, Hu P, Wu K, Zeng M. Optimal time-jerk trajectory planning for industrial robots. Mechanism and Machine Theory. 2018 Mar 1;121:530-44.

Gasparetto A, Zanotto V. A technique for time-jerk optimal planning of robot trajectories. Robotics and Computer-Integrated Manufacturing. 2008 Jun 1;24(3):415-26.

Fang Y, Qi J, Hu J, Wang W, Peng Y. An approach for jerk-continuous trajectory generation of robotic manipulators with kinematical constraints. Mechanism and Machine Theory. 2020 Nov 1;153:103957.

Suriano L, Otero A, et al. Exploiting multi-level parallelism for run-time adaptive inverse kinematics on heterogeneous mpsocs. IEEE Access. 2020 Jun 26;8:118707-24.

Zhao L, Jiang Z, Sun Y, et al. Collision-free kinematics for hyper-redundant manipulators in dynamic scenes using optimal velocity obstacles. International Journal of Advanced Robotic Systems. 2021 Feb 28;18(1):1729881421996148.

Mishra UA, Chawla I, Pathak PM. On determining shortest path in joint space of a cable-driven parallel robot for point-to-point motion. In2020 28th Mediterranean Conference on Control and Automation (MED) 2020 Sep 15 (pp. 984-989). IEEE.

Zhou J, Cao H, Jiang P, et al. Energy-saving trajectory planning for robotic high-speed milling of sculptured surfaces. IEEE Transactions on Automation Science and Engineering. 2021 Mar 24;19(3):2278-94.




DOI: https://doi.org/10.37628/ijra.v8i2.1514

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