Recent Advancements in Autonomous Robots and Their Technical Analysis

Table 2

Limitations of previously proposed techniques for UUVs.

Techniques	Applied on	Limitations	References
Self-tuning fuzzy proportional integral derivative (PID) nonsingular fast terminal sliding mode control (STF-PID-NFTSM)	PUMA560 robotic manipulator	(1) The average convergence time is 3.5 seconds in the presence of uncertainties; (2) The response experiences an undershoot in the presence of unmodeled uncertainties	[7]
Nonlinear disturbance observer-based sliding mode control law	UUV with 2 DOF manipulator	(1) The proposed UUV is a fully actuated system and thus consumes huge power and process time; (2) It has a small working envelope and does not consider unmodeled dynamic factors; (3) For estimating the sudden hydrodynamic coefficients, the strategy is complex	[39]
Bioinspired dolphin algorithm embedded with disturbance rejection scheme	UUV with fins like a dolphin	(1) The disturbance taken in the simulation is limited up to; (2) Undersea there are so many other factors, that is, hydrodynamic coefficients which were assumed through ANSYS and computational fluid dynamics	[11]
Adaptive iterative approach with boundary layer and hyperbolic tangent function	2nd-order nonlinear system	(1) Bounded conditions have been defined already; (2) Control input somehow experiences the chattering-like noise	[6]
Underwater long-arm manipulator (ULAM) with an improved hydraulic driving system (SHDS) with fuzzy-based PID control	UUV with long-arm gripper/manipulator	(1) Either in low or in high pressure, there is an average tracking error of 5.12 percent; (2) Each joint experiences an average overshoot of 1.5% and a steady-state error of 0.015; (3) Fuzzy-based PID slows down the maneuverability and increases hardware cost	[43]
The nonlinear model-based observer design using the linearization of the model to estimate the current state	UUV Visor3	(1) Chattering effect is available along with some transient and steady-state issues; (2) Hardware implementation will be costly as compared to other previously proposed UUVs	[40]
DexROV, an EC Horizon 2020-funded project	UUV with TITAN4 from shilling robotics	(1) The output response, that is, angular and translational velocities, experiences a chattering effect too with reasonable tracking error because of a long length of gripper and time delays	[38]
Hybrid high-order terminal sliding mode (HHOTSM) control approach for (MIMO) uncertain nonlinear systems	Underwater robotic manipulator	(1) First convergence time but output has a response which has some overshoots too; (2) Chattering is still there due to switching mode b/w terminal SMC and higher-order SMC	[16]
Sliding mode control-based dynamic positioning system	Applied on ship model in the deep sea	(1) parameters were assumed for fully loaded and ballasted conditions and did not consider unmodeled dynamic factors; (2) Responses, that is, surge, sway, and yaw, experience 12%–20% overshoots in simulations and experimental work, respectively	[14]
Supervisory feedforward artificial neural network- (ANN-) based fuzzy control law to address friction and elasticity issues of a manipulator	Flexible joint-based manipulator design	(1) There is a reasonable error in load and the motor trajectories; (2) The convergence rate on the time axis is not suitable for any sensitive pick and drop tasks; (3) The technique is based on ANN and a fuzzy set of rules; it will only be implemented on field-programmable gate array (FPGA) or digital signal processing (DSP) kits that lead us to an expensive hardware design	[5]
PID guidance and control laws to perform basic control tasks such as autoheading, autospeed, and straight line	Unmanned surface vehicle	(1) Time delays due to Global Positioning System- (GPS-) based communication.; (2) Due to these time delays, the responses have tracking errors	[13]