Slip-aware Model Predictive optimal control for Path following

Rajagopalan, Venkataramanan; Meriçli, Çetin; Kelly, Alonzo

doi:10.1109/icra.2016.7487659

Cited by 23 publications

(7 citation statements)

References 9 publications

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“…[23]. One notable work in this direction includes a model predictive optimal control presented by Rajagopalan et al [24]. The approach essentially used a Pure Pursuit Path Follower to generate the desired control commands along with an linear-quadratic regulator tracker to handle the effects of slip as disturbance by modifying the control inputs.…”

Section: Literature Reviewmentioning

confidence: 99%

Active Disturbance Rejection Control for Handling Slip in Tracked Vehicle Locomotion

Sebastian

Ben-Tzvi

2019

Journal of Mechanisms and Robotics

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This paper describes the use of an active disturbance rejection controller (ADRC) to estimate and compensate for the effect of slip in an online manner to improve the path tracking performance of autonomous ground vehicles (AGVs). AGVs with skid-steer locomotion mode are extensively used for robotic applications in the fields of agriculture, transportation, construction, warehouse maintenance, and mining. Majority of these applications such as performing reconnaissance and rescue operations in rough terrain or autonomous package delivery in urban scenarios, require the system to follow a path predetermined by a high-level planner or based on a predefined task. In the absence of effective slip estimation and compensation, the AGVs, especially tracked vehicles, can fail to follow the path as given out by the high-level planner. The proposed ADRC architecture uses a generic mathematical model that can account for the scaling and shift in the states of the system due to the effects of slip through augmented parameters. An extended Kalman filter (EKF) observer is used to estimate the varying slip parameters online. The estimated parameters are then used to compensate for the effects of slip at each iteration by modifying the control actions given by a low-level path tracking controller. The proposed approach is validated through experiments over flat and uneven terrain conditions including asphalt, vinyl flooring, artificial turf, grass, and gravel using a tracked skid-steer mobile robot. A detailed discussion on the results and directions for future research is also presented.

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Section: Literature Reviewmentioning

confidence: 99%

Active Disturbance Rejection Control for Handling Slip in Tracked Vehicle Locomotion

Sebastian

Ben-Tzvi

2019

Journal of Mechanisms and Robotics

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“…Their proposed path following solution is experimentally evaluated at speeds up to 1 m/s. Path following which takes wheel slip into account was proposed in Rajagopalan et al (2016), where the maximum speed of the robot in the experiments reaches 1 m/s. In Ostafew et al (2016), tracking of manually defined paths with constraints using a learning-based nonlinear model predictive control (NMPC) is done with skid-steered vehicles at speeds up to 2 m/s.…”

Section: Introductionmentioning

confidence: 99%

High-speed path following control of skid-steered vehicles

Huskic

Buck

Herrb

et al. 2019

The International Journal of Robotics Research

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We present a robust control scheme for skid-steered vehicles that enables high-speed path following on challenging terrains. First, a kinematic model with experimentally identified parameters is constructed to describe the terrain-dependent motion of skid-steered vehicles. Using Lyapunov theory, a nonlinear control law is defined, guaranteeing the convergence of the vehicle to the path. To allow smooth and accurate motion at higher speeds, an additional linear velocity control scheme is proposed, which takes actuator saturation, path following error, and reachable curvatures into account. The combined solution is experimentally evaluated and compared against two state-of-the-art algorithms, by using two different robots on several different terrain types, at different speeds. A Robotnik Summit XL robot is tested on three different terrain types and two different paths at speeds up to [Formula: see text] m/s. A Segway RMP 440 robot is tested on three different terrain types and two different path types at speeds up to [Formula: see text] m/s.

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“…Moreover, it has been suggested that look‐ahead distance is easier to tune than the parameters of the PID controller [36]. To consider the effect of slip angle at higher velocities, in [38], a receding horizon optimal control technique in addition to the PPC was used to handle the effect of wheel slip.…”

Section: Control Strategiesmentioning

confidence: 99%

Review and performance evaluation of path tracking controllers of autonomous vehicles

Rokonuzzaman

Mohajer

Nahavandi

et al. 2021

IET Intelligent Trans Sys

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Autonomous Vehicles (AVs) have shown indelible and revolutionary effects on accident reduction and more efficient use of travel time, with outstanding socio‐economic impact. Despite these benefits, to make AVs accepted by a wide demographic and produce them on an industrial scale with a reasonable price, there are still a number of technological and social challenges that need to be tackled. Path Tracking Controller (PTC) of AVs is one of the high potential subsystems that can be further improved in order to achieve more accurate, robust and comfortable tracking performance. This study provides a critical review and simulation study of several selected techniques used for the design of PTC of AVs. The AVs are assumed to have limited controllability due to non‐holonomic constraints, such as car‐like vehicles and differential drive mobile robots. A detailed discussion will be provided on the simulation outcomes as well as the pros and cons of each technique for the sake of implementation and improvement of state‐of‐the‐art PTC.

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Slip-aware Model Predictive optimal control for Path following

Cited by 23 publications

References 9 publications

Active Disturbance Rejection Control for Handling Slip in Tracked Vehicle Locomotion

Active Disturbance Rejection Control for Handling Slip in Tracked Vehicle Locomotion

High-speed path following control of skid-steered vehicles

Review and performance evaluation of path tracking controllers of autonomous vehicles

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