![References:
1. MarathonWorld. (2012). [Online]. Available: http://www.marathonworld.com
2. I. J. Cox and S. L. Hingorani, “An efficient implementation of Reid’s multiple
hypothesis tracking algorithm and its evaluation for the purpose of visual
tracking,” IEEE Trans. Pattern Anal.Mach. Intell., vol. 18, no. 2, pp. 138–150,
Feb. 1996.
3. J. K. Aggarwal and Q. Cai, “Human motion analysis: A review,” in Proc. IEEE Proc.
Nonrigid Articulated Motion Workshop, 1997, pp. 90–102.
4. J. MacCormick and A. Blake, “A probabilistic exclusion principle for tracking
multiple objects,” in Proc. 7th IEEE Int. Conf. Comput. Vision, 1999, pp. 572–
578.](https://image.slidesharecdn.com/developmentofimageprocessingbasedhumantrackingandcontrolalgorithmforaservicerobot-150623170322-lva1-app6891/85/Development-of-image-processing-based-human-tracking-and-control-algorithm-for-a-service-robot-17-320.jpg){kind=tracking}
Development of image processing based human tracking and control algorithm for a service robot
- 1. Development of Image Processing based Human Tracking and Control Algorithm for A Service Robot
- 2. Abstract: This paper presents a human detection algorithm and an obstacle avoidance algorithm for a service robot that provides a service tracking. The mobile robot will have the ability to follow a human and avoid dynamically moving obstacles in an unstructured outdoor environment. To detect a human by an Image processing, we defined features of the human body in xml file and employed a support vector data description method. In order to avoid moving obstacles while tracking a person, we defined an ultrasonic obstacle sensor, each obstacle using the relative distance between the robot and an obstacle. For smoothly by passing obstacles without collision, a dynamic obstacle avoidance algorithm for the service robot is implemented, which directly employed a real-time position vector between the robot and the shortest path around the obstacle.
- 3. Objective: An Image processing based system is used to detect objects and to follow the path of the environment in robotic systems .In this project, we use a Image processing algorithm to detect a human. The Camera is placed on the robot at torso height and scans an environment at this height. Whenever a human is detected, we use pattern recognition of various shapes in clustered data scanned from a human torso.
- 4. Existing Method: Proposed Method: In the proposed method we will use Opencv image processing library in order to detect the Human body in the video and track him accordingly where as an ultrasonic sensor will used in order to detect the body distance from the robot and any obstacle present and act accordingly. In the existing method, the concept implemented was based on a non reliable technology in real time, where in an outdoor environment there are more disadvantages that the system can mislead if more humans are in its path.
- 5. ARM 11 USB camera5V DC SUPPLY L293D Motors Ultrasonic sensor BLOCK DIAGRAM
- 6. An ARM 11 architecture based Raspberry pi board is used to implemented the concept, a USB camera will be connected to the board. Using Open Source Computer Vision library (OpenCV) will train the human body shape and structure to the program. Whenever a Human body is present in from the camera, the algorithm will detect it and draw a rectangular around the body for identification and starts its movements. Obstacle Avoidance: If any obstacle is located between a marathoner and the MSR and is moving slower than the MSR, avoiding the obstacle will be done using the ultrasonic sensor and simultaneously the robot will be tracking the human.
- 7. ARM stands for Advanced RISC Machine The ARM11 is based on the ARMv6 instruction set architecture Bi-endian – can operate in either little-endian or big-endian format Most devices today use little-endian Actually uses two instruction sets – the 32-bit ARM and the 16-bit Thumb
- 8. Raspberry Pi is a credit-card sized computer that plugs into your TV and a keyboard. It is a capable little computer which can be used in electronics projects, and for many of the things that your desktop PC does, like spreadsheets, word-processing and games. It also plays high-definition video. We want to see it being used by kids all over the world to learn how computers work, how to manipulate the electronic world around them, and how to program.
- 9. r0 r1 r2 r3 r4 r5 r6 r7 r8 r9 r10 r11 r12 r13 (sp) r14 (lr) r15 (pc) cpsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r8 r9 r10 r11 r12 r13 (sp) r14 (lr) spsr FIQ IRQ SVC Undef Abort User Mode r0 r1 r2 r3 r4 r5 r6 r7 r8 r9 r10 r11 r12 r13 (sp) r14 (lr) r15 (pc) cpsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r8 r9 r10 r11 r12 r13 (sp) r14 (lr) spsr Current Visible Registers Banked out Registers FIQ IRQ SVC Undef Abort r0 r1 r2 r3 r4 r5 r6 r7 r15 (pc) cpsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r8 r9 r10 r11 r12 r13 (sp) r14 (lr) spsr Current Visible Registers Banked out Registers User IRQ SVC Undef Abort r8 r9 r10 r11 r12 r13 (sp) r14 (lr) FIQ ModeIRQ Mode r0 r1 r2 r3 r4 r5 r6 r7 r8 r9 r10 r11 r12 r15 (pc) cpsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r8 r9 r10 r11 r12 r13 (sp) r14 (lr) spsr Current Visible Registers Banked out Registers User FIQ SVC Undef Abort r13 (sp) r14 (lr) Undef Mode r0 r1 r2 r3 r4 r5 r6 r7 r8 r9 r10 r11 r12 r15 (pc) cpsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r8 r9 r10 r11 r12 r13 (sp) r14 (lr) spsr Current Visible Registers Banked out Registers User FIQ IRQ SVC Abort r13 (sp) r14 (lr) SVC Mode r0 r1 r2 r3 r4 r5 r6 r7 r8 r9 r10 r11 r12 r15 (pc) cpsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r8 r9 r10 r11 r12 r13 (sp) r14 (lr) spsr Current Visible Registers Banked out Registers User FIQ IRQ Undef Abort r13 (sp) r14 (lr) Abort Mode r0 r1 r2 r3 r4 r5 r6 r7 r8 r9 r10 r11 r12 r15 (pc) cpsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r13 (sp) r14 (lr) spsr r8 r9 r10 r11 r12 r13 (sp) r14 (lr) spsr Current Visible Registers Banked out Registers User FIQ IRQ SVC Undef r13 (sp) r14 (lr)
- 10. r8 r9/sb r10/sl r11 r12 r13/sp r14/lr r15/pc r0 r1 r2 r3 r4 r5 r6 r7Register variables Must be preserved Arguments into function Result(s) from function otherwise corruptible (Additional parameters passed on stack) Scratch register (corruptible) Stack Pointer Link Register Program Counter The compiler has a set of rules known as a Procedure Call Standard that determine how to pass parameters to a function (see AAPCS) CPSR flags may be corrupted by function call. Assembler code which links with compiled code must follow the AAPCS at external interfaces The AAPCS is part of the new ABI for the ARM Architecture Register - Stack base - Stack limit if software stack checking selected - R14 can be used as a temporary once value stacked - SP should always be 8-byte (2 word) aligned
- 11. Camera plays a vital role in automation purpose. The camera is used for monitoring of a room from a remote place. The camera used is a USB camera. Whenever the user clicks on to video button on loaded webpage, the corresponding room video will be streamed on to webpage .For this purpose we use a MJPG streamer. The below figure shows the camera that has been used for monitoring of a room.
- 12. The sensor is primarily intended to be used in security systems for detection of moving objects, but can be effectively involved in intelligent children’s toys, automatic door opening devices, and sports training and contact- less-speed measurement equipment.
- 13. This chip contains 4 enable pins. Each enable pin corresponds to 2 inputs. Based on the input values given, the device connected to this IC works accordingly.
- 14. motors are used to efficiently convert electrical energy into mechanical energy. Magnetism is the basis of their principles of operation. They use permanent magnets, electromagnets and exploit the magnetic properties of materials in order to create these amazing machines DC Motor
- 15. Implementation: Obstacle Avoidance: If any obstacle is located between a marathoner and the MSR and is moving slower than the MSR, avoiding the obstacle will be done using the ultrasonic sensor and simultaneously the robot will be tracking the human. An ARM 11 architecture based Raspberry pi board is used to implemented the concept, a USB camera will be connected to the board. Using Open Source Computer Vision library (OpenCV) will train the human body shape and structure to the program. Whenever a Human body is present in from the camera, the algorithm will detect it and draw a rectangular around the body for identification and starts its movements.
- 16. Applications: Conclusion: Advantages: Security Industry High Accuracy Easy to implement A marathoner service robotic system will be designed for human detection . When the intruder is in front of the sensor than the MSR, the MSR does not consider the intruder as an obstacle but using the algorithm identifies the human body. Therefore, the MSR did not show any avoidance behavior. By applying the modified technique an advanced system will be developed.
- 17. References: 1. MarathonWorld. (2012). [Online]. Available: http://www.marathonworld.com 2. I. J. Cox and S. L. Hingorani, “An efficient implementation of Reid’s multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking,” IEEE Trans. Pattern Anal.Mach. Intell., vol. 18, no. 2, pp. 138–150, Feb. 1996. 3. J. K. Aggarwal and Q. Cai, “Human motion analysis: A review,” in Proc. IEEE Proc. Nonrigid Articulated Motion Workshop, 1997, pp. 90–102. 4. J. MacCormick and A. Blake, “A probabilistic exclusion principle for tracking multiple objects,” in Proc. 7th IEEE Int. Conf. Comput. Vision, 1999, pp. 572– 578.