Object following and obstacle avoidance using a laser scanner in the outdoor mobile robot Auriga-α

Martínez, Jorge L.; Pozo-Ruz, Ana; Pedraza, S.; Fernández, Raúl

doi:10.1109/iros.1998.724620

Cited by 18 publications

(13 citation statements)

References 14 publications

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“…While implicit path is defined by perceivable features in the environment with an appropriate set of sensor, basically a camera. Examples given by other researchers includes: A route determines a path that is recognized as an image by its left and right edges [7], an object course can be detected as point clusters in consecutive range scans [8]. Therefore, computational tracking error with respect to an implicit path does not require global position calculations, but rather the path is determined by the processing of the images taken by the camera.…”

Section: Classification Of Path Of Mobile Robotmentioning

confidence: 99%

A Review of some Pure-Pursuit based Path Tracking Techniques for Control of Autonomous Vehicle

Samuel¹,

Hussein²,

Mohamad³

2016

IJCA

124

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This paper gives a brief review of few common path tracking techniques used in the design of autonomous vehicles. Technique such as pure-pursuit, vector pursuit as well as CFpursuit which are all based on the pure-pursuit techniques were discussed and a detailed comparism was made between these geometric techniques. Also this review work discusses areas were little research has been done. Areas such as tracking of an implicit part of a mobile robot and proposes an area where feature research can be done such as tracking of both implicit and explicit path for a non-holonomic mobile robot.

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Section: Classification Of Path Of Mobile Robotmentioning

confidence: 99%

A Review of some Pure-Pursuit based Path Tracking Techniques for Control of Autonomous Vehicle

Samuel¹,

Hussein²,

Mohamad³

2016

IJCA

124

View full text Add to dashboard Cite

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“…Practically, there will be a small translation factor between the coordinate axis system of the Kinect and the center of mass of the follower robot, which barely affects the steering mechanism, while the speed control has an equivalent parameter that can be tuned. The calculation of the angle to the master robot is given by Equations (3)- (6). The superscript F denotes the follower (Kinect) frame of reference, while the sub-script L stands for the leader robot.…”

Section: Visionmentioning

confidence: 99%

Vision-Based Robot Following Using PID Control

Pati

Kala

2017

Technologies

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Abstract:Applications like robots which are employed for shopping, porter services, assistive robotics, etc., require a robot to continuously follow a human or another robot. This paper presents a mobile robot following another tele-operated mobile robot based on a PID (Proportional-Integral-Differential) controller. Here, we use two differential wheel drive robots; one is a master robot and the other is a follower robot. The master robot is manually controlled and the follower robot is programmed to follow the master robot. For the master robot, a Bluetooth module receives the user's command from an android application which is processed by the master robot's controller, which is used to move the robot. The follower robot receives the image from the Kinect sensor mounted on it and recognizes the master robot. The follower robot identifies the x, y positions by employing the camera and the depth by using the Kinect depth sensor. By identifying the x, y, and z locations of the master robot, the follower robot finds the angle and distance between the master and follower robot, which is given as the error term of a PID controller. Using this, the follower robot follows the master robot. A PID controller is based on feedback and tries to minimize the error. Experiments are conducted for two indigenously developed robots; one depicting a humanoid and the other a small mobile robot. It was observed that the follower robot was easily able to follow the master robot using well-tuned PID parameters.

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“…The position and direction of person's feet would be calculated in "both feet still" period of a person's walking model [22] shown in Figure 3. One method is introduced to follow a moving object [25]. Another method is also introduced to follow a walking person with a single laser range scanner on a mobile robot [26], in which the motion of a person's leg is detected using the Support Vector domain description method proposed in [27] and an e cient leg-tracking scheme by exploiting a human walking model is established.…”

Section: Related Workmentioning

confidence: 99%

A Walking Training System with Customizable Trajectory Designing

Dong

Matsumaru

2014

Paladyn, Journal of Behavioral Robotics

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This paper shows a novel walking training system for foot-eye coordination. To design customizable trajectories for di erent users conveniently in walking training, a new system which can track and record the actual walking trajectories by a tutor and can use these trajectories for the walking training by a trainee is developed. We set the four items as its human-robot interaction design concept: feedback, synchronization, ingenuity and adaptability. A foot model is proposed to de ne the position and direction of a foot. The errors in the detection method used in the system are less than 40 mm in position and 15 deg in direction. On this basis, three parts are structured to achieve the system functions: Trajectory Designer, Trajectory Viewer and Mobile Walking Trainer. According to the experimental results, we have con rmed the system works as intended and designed such that the steps recorded in Trajectory Designer could be used successfully as the footmarks projected in Mobile Walking Trainer and foot-eye coordination training would be conducted smoothly.

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Object following and obstacle avoidance using a laser scanner in the outdoor mobile robot Auriga-α

Cited by 18 publications

References 14 publications

A Review of some Pure-Pursuit based Path Tracking Techniques for Control of Autonomous Vehicle

A Review of some Pure-Pursuit based Path Tracking Techniques for Control of Autonomous Vehicle

Vision-Based Robot Following Using PID Control

A Walking Training System with Customizable Trajectory Designing

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