Channavva Kolanur

@kletech.ac.in

Assistant Professor and Automation & Robotics
KLE Technological University

Channavva Kolanur


               Download Compact PDF  
https://researchid.co/cb.kolanur

RESEARCH, TEACHING, or OTHER INTERESTS

Engineering, Multidisciplinary, Engineering, Engineering
9

Scopus Publications

57

Scholar Citations

4

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • Practice-Based Learning in Control Systems Design a Pedagogical Framework for Enhanced Engineering Education
    , C B Kolanur, Rakesh P. Tapaskar, , Vinodkumar. V. Meti, , A. C. Giriyapur, , Sachin Karadagi, and
    Journal of Engineering Education Transformations, 2026
    The integration of practice-based learning (PBL) methodologies into engineering curricula is increasingly recognized for its potential to bridge the gap between theoretical instruction and practical application. This study presents the redesign and implementation of a Control Systems Design course at the undergraduate level, integrating PBL and problem-based learning strategies with a strong emphasis on experiential engagement. The course employed modern tools such as MATLAB, Simulink, and Virtual Labs, along with hardware-in-the-loop (HIL) systems, to facilitate simulation-based modeling, real-time implementation, and collaborative learning.The Quantitative evaluation revealed a 3.59% improvement in average academic performance, as measured by weighted semester-end grades, and a 1.62% increase in Course Outcome attainment, particularly in simulation proficiency and problem-solving skills. Additionally, structured student feedback based on a 5-point Likert scale demonstrated a mean improvement of 0.82 points, representing a 20.5% enhancement in perceived learning effectiveness, with significant gains in pedagogical clarity and hands-on learning components. Qualitative observations further supported a 35% increase in teamwork and communication effectiveness, as evidenced by peer-assessed project evaluations and group activities.The findings substantiate the pedagogical value of integrating practice-based learning into core engineering courses. The approach not only improved academic outcomes and engagement but also strengthened professional competencies essential for modern engineering practice. The study provides a replicable framework for engineering educators seeking to align curriculum design with Outcome-Based Education (OBE), industry expectations, and future-ready learning environments
  • Design of a Low-Cost IoT-based Call-Triggered Agricultural Automation System
    Mohammed Yunus Mohammed Gouse Khatib, Prajwal Panadi, C. B. Kolanur, Sohansingh S Thakur, Amogh Bhuti
    Proceedings of 4th International Conference on Electronics and Renewable Systems Icears 2026, 2026
  • An Overview of Collision-Free Path Planning Techniques for Industrial Autonomous Robots
    C. B. Kolanur, Jyoti Bali, Shilpa Tanvashi, Arunkumar Giriyapur
    Cyber Physical Systems Applications Challenges and Research Directions, 2025
    One of the most important research questions in industrial and humanoid robotics in dynamic situations is collision and occlusion-free path planning (COFPP). The effectiveness and efficiency of the path planning algorithms are assessed under a variety of restrictions, such as dynamic and static environments with various levels of complexity. This chapter carries out a comparative analysis of collision-free path planning in industrial robots. Discussion is held regarding the effectiveness of various collision-free path planning algorithms, including Dijkstra, A*, Probabilistic Road Map, RRT, and RRT*, as well as their benefits and drawbacks.
  • Vision Guided Sorting of Medical Dissection Tools using a 3DOF SCARA Robot with Deep Learning Integration
    Shashank S, Ankita K Basutkar, Shivani, Sangamesh S, Prashant Pelli, Shilpa V Tanvashi, C B Kolanur
    2025 6th International Conference for Emerging Technology Incet 2025, 2025
    Integrating artificial intelligence with robotic systems has paved the way for innovative automation solutions across diverse domains. This study proposes sorting medical dissection tools using an innovative integrated system comprising computer vision and robots. The system employs a single conveyor line with a modified 3-degree-of-freedom (3DOF) SCARA robot to pick and place the dissection tools from the conveyor to the respective bins. Computer vision and deep learning algorithms, precisely the YOLOv5 model, identify and categorize dissection tools in real-time. Deploying a 3DOF robotic arm enhances efficiency by sorting tools and placing them in designated locations based on their classes. Unlike conventional methods that use multiple conveyors, this approach significantly reduces infrastructure costs while simplifying the sorting process. This automated sorting method not only minimizes errors associated with manual sorting but also offers a cost-effective solution for manufacturing firms. Its adaptability makes it suitable for sorting a diverse range of dissection tools, contributing to increased operational efficiency and cost savings in manufacturing. This integrated, automated, vision-based system ensures efficient sorting with minimal error rates, making the system suitable for laboratory and surgical settings where accuracy and efficiency are paramount.
  • Integration of Computer Vision and 4DOF SCARA Robot Arm for Tomato Sorting
    Shilpa Tanvashi, C B Kolanur, P Shri Aakash, Tejas Muchchandi, Hrithik Dhongadi, Akarsh Hirennavar, Sanket Aralgundagi, Vaibhav Shreyakar
    2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024
    Automating fruit recognition and classification is an important computer vision application that can improve efficiency and consistency in the fruit industry. Manual sorting methods based on visual inspection are tedious, time-consuming, and prone to inconsistencies. This work presents the design and deployment of an automated tomato sorting system that integrates computer vision and robotics. The system classifies tomatoes into three maturity stages (Green, Half-ripe, Ripe) based on color using the YOLOv5 deep learning algorithm. A SCARA robot is used for picking and placing the sorted tomatoes into respective bins. The system demonstrates a fast inference time of 22.31 milliseconds for tomato detection and can sort three tomatoes of different maturity classes in approximately 1.2 seconds on average. This consistent and efficient sorting is based on objective color criteria rather than manual visual inspection. The system can help improve product quality, reduce labor costs, and increase throughput in tomato processing facilities. The approach can be extended to sorting other fruits and vegetables based on color attributes.
  • An overview of machine vision based quality control strategies for smart manufacturing
    C. B. Kolanur, Jyoti Bali, Shilpa Tanvashi, Arunkumar Giriyapur
    Aip Conference Proceedings, 2023
  • Lung Sound Based Pulmonary Disease Classification Using Deep Learning
    Madhu R. Koravanavar, C. B. Kolanur
    2023 2nd International Conference on Futuristic Technologies Incoft 2023, 2023
    Respiratory infections are disorders that damage the lungs and airways and make it difficult for patients to breathe. Any part of the respiratory system has the potential to become infected or sick, which could have a variety of negative effects. Early detection of lung disorders results in a person's successful treatment. Using electronically recorded lung sounds, pulmonary diseases can be diagnosed. MelFrequency Cepstral Coefficient (MFCC), one of the Librosa machine learning library features, is used to check that such a brief speech segment is sufficiently steady to permit effective modeling. In this research, Librosa is one of the better preprocessing techniques used when working with audio data. The CNN model is applied to the collected dataset and obtained a train accuracy of 95% and a test accuracy of 85% when trained on extracted MFCC features. And also used a number of performance evaluation indicators, including as F1score, accuracy, precision, and recall. The outcomes of this research enable the use of deep learning models in clinical settings to improve doctors' judgment when identifying lung disorders.
  • FPGA-Based Hardware Acceleration Using PYNQ-Z2
    Vineeth C Johnson, Jyoti Bali, Shilpa Tanvashi, C B Kolanur
    2023 2nd International Conference on Electrical Electronics Information and Communication Technologies Iceeict 2023, 2023
    A study on the FPGA development board PYNQ-Z2 for hardware acceleration is presented in this research paper. The experiment accelerates the tasks of optical character recognition (OCR) and image recognition using the FPGA on PYNQ-Z2. The output results on hardware acceleration (Processing system (PS) and Programmable Logic (PL)) are compared with the output results obtained while executing the same tasks on the Arm processor (Processing System (PS)) alone. In this experiment, a Long short-term memory (LSTM) neural network is used to implement OCR, and a Binarized neural network (BNN) is used to implement image recognition. LSTM and BNN here are quantized to reduce memory usage while implementing them on PYNQ-Z2.
  • Design of IoT based Platform Development for Smart Home Appliances Control
    C B Kolanur, R M Banakar, G Rajneesh
    Journal of Physics Conference Series, 2021
    The advent of industrial automation has brought about a substantial change in the human lifestyle and the way human interaction with machines. One of the major technological interventions in day-to-day life is the role of automation, which has uplifted the living standards in developed countries and fostered humans’ dependency for accomplishing recurring tasks. The latest and most adopted technology for remotely monitoring and controlling any machine or device is the Internet of Things-which has become one of the industry standards for automation. Multiple edge computation capable embedded devices and machines are connected to the internet as independent nodes, which can be monitored and controlled remotely with the use of IoT. Adapting this cutting-edge technology for household appliances to monitor and control them is often seen nowadays. This is fast and reliable but arrives with its own snags such as availability of internet at place where user and also the device/appliance is located, use of single control strategy which hampers and restricts the user always to carry the remote or to stay in the vicinity of the device to be controlled in case of wifi or Bluetooth controlled automation. The proposed research focuses on the adoption of multiple strategies to control each device/appliance to empower the end-user without being restricted to depend on a single strategy remote controlling system. The core part of the proposed research revolves around the Message Queuing Telemetry Transport (MQTT) protocol but can be activated with multiple routes such as touch-based sensing panels, cellphone-based controlling, web-enabled controlling or even gesture-based controlling of the appliances resulting in an ameliorative user experience and interactions with machines.

RECENT SCHOLAR PUBLICATIONS

  • Practice-Based Learning in Control Systems Design a Pedagogical Framework for Enhanced Engineering Education
    CB Kolanur, RP Tapaskar, VV Meti, AC Giriyapur, S Karadagi
    Journal of Engineering Education Transformations, 43-56 , 2026
    2026
    Citations: 1
  • Intelligent Tool Management System Using Dual Collaborative Robots: MyCobot 280-JN and MechArm 270-PI
    R Palthur, P Bidari, K Hiremath, K Modani, CB Kolanur, VN Kulkarni
    2026 International Conference on Smart Futuristic Technology, 1-8 , 2026
    2026
  • Assessing Traditional and Deep Learning Voice Recognition Models for Reliable Control of Robots in Dynamic Settings
    BB Kolanur, A Khyadad, R Palthur, RP Tapaskar, NS R
    EPJ Web of Conferences 367, 04003 , 2026
    2026
  • Vision Guided Sorting of Medical Dissection Tools using a 3DOF SCARA Robot with Deep Learning Integration
    S Shashank, AK Basutkar, S Sangamesh, P Pelli, SV Tanvashi, ...
    2025 6th International Conference for Emerging Technology (INCET), 1-6 , 2025
    2025
  • An Overview of Collision-Free Path Planning Techniques for Industrial Autonomous Robots
    CB Kolanur, J Bali, S Tanvashi, AG
    Cyber-Physical Systems Applications, Challenges, and Research Directions … , 2025
    2025
    Citations: 2
  • Integration of Computer Vision and 4DOF SCARA Robot Arm for Tomato Sorting
    S Tanvashi, CB Kolanur, PS Aakash, T Muchchandi, H Dhongadi, ...
    2024 15th International Conference on Computing Communication and Networking … , 2024
    2024
    Citations: 2
  • Inspection of Silk Cocoons using 3-DOF SCARA Robot for Quality Control
    CB Kolanur, S Tanvashi, P Asuti
    2024
    Citations: 3
  • Lung Sound Based Pulmonary Disease Classification Using Deep Learning
    M Koravannavar, CB Kolanur
    https://ieeexplore.ieee.org/search/searchresult.jsp?newsearch=true&queryText … , 2024
    2024
    Citations: 2
  • A Project-Based Learning Approach to Measurement Systems Laboratory for Undergraduate Students
    SIG CB. Kolanur, Vinod Kumar V. Meti , Amit Talli , A C Giriyapur , Prashant ...
    Journal of Engineering Education Transformations 37 (4), 36-45 , 2024
    2024
    Citations: 4
  • An overview of machine vision based quality control strategies for smart manufacturing
    CB Kolanur, J Bali, S Tanvashi, A Giriyapur
    AIP Conference proceedings 2788 (1), 10 , 2023
    2023
    Citations: 9
  • Fpga-based hardware acceleration using pynq-z2
    VC Johnson, J Bali, S Tanvashi, CB Kolanur
    2023 Second International Conference on Electrical, Electronics, Information … , 2023
    2023
    Citations: 9
  • Industry 4.0: intelligent quality control and surface defect detection
    VC Johnson, JS Bali, CB Kolanur, S Tanwashi
    3c Empresa: investigación y pensamiento crítico 11 (2), 214-220 , 2022
    2022
    Citations: 7
  • Design of iot based platform development for smart home appliances control
    CB Kolanur, RM Banakar, G Rajneesh
    Journal of Physics: Conference Series 1969 (1), 012052 , 2021
    2021
    Citations: 18

MOST CITED SCHOLAR PUBLICATIONS

  • Design of iot based platform development for smart home appliances control
    CB Kolanur, RM Banakar, G Rajneesh
    Journal of Physics: Conference Series 1969 (1), 012052 , 2021
    2021
    Citations: 18
  • An overview of machine vision based quality control strategies for smart manufacturing
    CB Kolanur, J Bali, S Tanvashi, A Giriyapur
    AIP Conference proceedings 2788 (1), 10 , 2023
    2023
    Citations: 9
  • Fpga-based hardware acceleration using pynq-z2
    VC Johnson, J Bali, S Tanvashi, CB Kolanur
    2023 Second International Conference on Electrical, Electronics, Information … , 2023
    2023
    Citations: 9
  • Industry 4.0: intelligent quality control and surface defect detection
    VC Johnson, JS Bali, CB Kolanur, S Tanwashi
    3c Empresa: investigación y pensamiento crítico 11 (2), 214-220 , 2022
    2022
    Citations: 7
  • A Project-Based Learning Approach to Measurement Systems Laboratory for Undergraduate Students
    SIG CB. Kolanur, Vinod Kumar V. Meti , Amit Talli , A C Giriyapur , Prashant ...
    Journal of Engineering Education Transformations 37 (4), 36-45 , 2024
    2024
    Citations: 4
  • Inspection of Silk Cocoons using 3-DOF SCARA Robot for Quality Control
    CB Kolanur, S Tanvashi, P Asuti
    2024
    Citations: 3
  • An Overview of Collision-Free Path Planning Techniques for Industrial Autonomous Robots
    CB Kolanur, J Bali, S Tanvashi, AG
    Cyber-Physical Systems Applications, Challenges, and Research Directions … , 2025
    2025
    Citations: 2
  • Integration of Computer Vision and 4DOF SCARA Robot Arm for Tomato Sorting
    S Tanvashi, CB Kolanur, PS Aakash, T Muchchandi, H Dhongadi, ...
    2024 15th International Conference on Computing Communication and Networking … , 2024
    2024
    Citations: 2
  • Lung Sound Based Pulmonary Disease Classification Using Deep Learning
    M Koravannavar, CB Kolanur
    https://ieeexplore.ieee.org/search/searchresult.jsp?newsearch=true&queryText … , 2024
    2024
    Citations: 2
  • Practice-Based Learning in Control Systems Design a Pedagogical Framework for Enhanced Engineering Education
    CB Kolanur, RP Tapaskar, VV Meti, AC Giriyapur, S Karadagi
    Journal of Engineering Education Transformations, 43-56 , 2026
    2026
    Citations: 1
  • Intelligent Tool Management System Using Dual Collaborative Robots: MyCobot 280-JN and MechArm 270-PI
    R Palthur, P Bidari, K Hiremath, K Modani, CB Kolanur, VN Kulkarni
    2026 International Conference on Smart Futuristic Technology, 1-8 , 2026
    2026
  • Assessing Traditional and Deep Learning Voice Recognition Models for Reliable Control of Robots in Dynamic Settings
    BB Kolanur, A Khyadad, R Palthur, RP Tapaskar, NS R
    EPJ Web of Conferences 367, 04003 , 2026
    2026
  • Vision Guided Sorting of Medical Dissection Tools using a 3DOF SCARA Robot with Deep Learning Integration
    S Shashank, AK Basutkar, S Sangamesh, P Pelli, SV Tanvashi, ...
    2025 6th International Conference for Emerging Technology (INCET), 1-6 , 2025
    2025