Targeted Object Striking for a 7-DoF Manipulator: A Residual Learning Approach
Rishin Chakraborty,Priyansh Sinha,Samarth Brahmbhatt,Nagamanikandan Govindan
Advances in Robotics, AIR, 2025
@inproceedings{bib_Targ_2025, AUTHOR = {Rishin Chakraborty, Priyansh Sinha, Samarth Brahmbhatt, Nagamanikandan Govindan}, TITLE = {Targeted Object Striking for a 7-DoF Manipulator: A Residual Learning Approach}, BOOKTITLE = {Advances in Robotics}. YEAR = {2025}}
As robotic manipulators start performing more daily tasks, striking can be a useful method for transporting objects because it significantly increases the reachable workspace. However, striking methods are underexplored compared to pick-and-place because of the difficulty of modeling and executing striking interactions.
In this paper, we develop an algorithm for striking objects so that they stop at a target location. We start with an optimizer in simulation that solves for the striking velocity given the relative target position, and perform system identification to set the simulation parameters. However, real-world striking with this model does not have high accuracy because it is unclear which parameters should be considered for identification in practice. Therefore, we finally developed a residual learning approach that subsumes all unmodeled differences between the simulation and the real-world environment into action, that is, striking velocity residuals. Our real-world experiments show that the residual learning model results in 81.6% more accurate object strikes.
WireFlie: A Novel Obstacle-Overcoming Mechanism for Autonomous Transmission Line Inspection Drones
Aditya Sehgal,Zahiruddin Mahammad,Poorna Sasank Sesetti,Ankur Badhwar,Nagamanikandan Govindan
IEEE Robotics and Automation Letters, RAL, 2025
@inproceedings{bib_Wire_2025, AUTHOR = {Aditya Sehgal, Zahiruddin Mahammad, Poorna Sasank Sesetti, Ankur Badhwar, Nagamanikandan Govindan}, TITLE = {WireFlie: A Novel Obstacle-Overcoming Mechanism for Autonomous Transmission Line Inspection Drones}, BOOKTITLE = {IEEE Robotics and Automation Letters}. YEAR = {2025}}
Robotic inspection of transmission lines presents significant challenges due to the complexity of navigating along the wires. Existing systems often rely on either flight modes for visual inspection or articulated crawling mechanisms for contact-based inspection. However, these approaches face limitations in effectively bypassing in-line obstacles or pylons, which are common in transmission line environments. This letter presents WireFlie, a novel hybrid robotic system that integrates rolling and flight modes to overcome these challenges. The system consists of a pair of underactuated arms mounted on a drone platform, designed for secure, collision-free locking and detaching, enabling seamless transitions between locomotion modes. WireFlie supports both single-arm and dual-arm rolling, allowing it to bypass in-line obstacles such as Stockbridge dampers, dual spacers, and sleeves, and to overcome larger obstacles like pylons using flight. Additionally, we propose a high-level controller for autonomous locking, detaching, and obstacle avoidance. Experiments are conducted on a custom-made setup that closely resembles a transmission wire. We evaluate both the design and control aspects of our system, with results including kinematic analysis, wire detection, autonomous locking and the corresponding trajectory, and obstacle detection and avoidance strategies. This research contributes to the field of robotic infrastructure inspection by merging aerial and wire-based locomotion, providing efficient and autonomous monitoring of power lines.
DG16M: A Large-Scale Dataset for Dual-Arm Grasping with Force-Optimized Grasps
Md Faizal Karim,Mohammed Saad Hashmi,Bollimuntha Shreya,Mahesh Reddy Tapeti,Gaurav Singh,Nagamanikandan Govindan,K Madhava Krishna
International Conference on Intelligent Robots and Systems, IROS, 2025
@inproceedings{bib_DG16_2025, AUTHOR = {Md Faizal Karim, Mohammed Saad Hashmi, Bollimuntha Shreya, Mahesh Reddy Tapeti, Gaurav Singh, Nagamanikandan Govindan, K Madhava Krishna}, TITLE = {DG16M: A Large-Scale Dataset for Dual-Arm Grasping with Force-Optimized Grasps}, BOOKTITLE = {International Conference on Intelligent Robots and Systems}. YEAR = {2025}}
Dual-arm robotic grasping is crucial for handling large objects that require stable and coordinated manipulation. While single-arm grasping has been extensively studied, datasets tailored for dual-arm settings remain scarce. We introduce a large-scale dataset of 16 million dual-arm grasps, evaluated under improved force-closure constraints. Additionally, we develop a benchmark dataset containing 300 objects with approximately 30,000 grasps, evaluated in a physics simulation environment, providing a better grasp quality assessment for dual-arm grasp synthesis methods. Finally, we demonstrate the effectiveness of our dataset by training a Dual-Arm Grasp Classifier network that outperforms the state of-the-art methods by 15%, achieving higher grasp success rates and improved generalization across objects.
DA-VIL: Adaptive Dual-Arm Manipulation with Reinforcement Learning and Variable Impedance Control
Md Faizal Karim,Bollimuntha Shreya,Mohammed Saad Hashmi,Autrio Das,Gaurav Singh,Srinath Sridhar,Arun Kumar Singh,Nagamanikandan Govindan,K Madhava Krishna
International Conference on Robotics and Automation, ICRA, 2025
@inproceedings{bib_DA-V_2025, AUTHOR = {Md Faizal Karim, Bollimuntha Shreya, Mohammed Saad Hashmi, Autrio Das, Gaurav Singh, Srinath Sridhar, Arun Kumar Singh, Nagamanikandan Govindan, K Madhava Krishna}, TITLE = {DA-VIL: Adaptive Dual-Arm Manipulation with Reinforcement Learning and Variable Impedance Control}, BOOKTITLE = {International Conference on Robotics and Automation}. YEAR = {2025}}
Dual-arm manipulation is an area of growing interest in the robotics community. Enabling robots to perform tasks that require the coordinated use of two arms, is essential for complex manipulation tasks such as handling large objects, assembling components, and performing human-like interactions. However, achieving effective dual-arm manipulation is challenging due to the need for precise coordination, dynamic adaptability, and the ability to manage interaction forces between the arms and the objects being manipulated. We propose a novel pipeline that combines the advantages of policy learning based on environment feedback and gradient-based optimization to learn controller gains required for the control outputs. This allows the robotic system to dynamically modulate its impedance in response to task demands, ensuring stability and dexterity in dual-arm operations. We evaluate our pipeline on a trajectory-tracking task involving a variety of large, complex objects with different masses and geometries. The performance is then compared to three other established methods for controlling dual-arm robots, demonstrating superior results.
Hierarchical Manipulation Planning Framework Combining Striking, Pushing and Pick & Place Motion Primitives
Priyansh Sinha,Prakrut Kotecha,Nagamanikandan Govindan
International Conference on Automation Science and Engineering, ICASE, 2024
@inproceedings{bib_Hier_2024, AUTHOR = {Priyansh Sinha, Prakrut Kotecha, Nagamanikandan Govindan}, TITLE = {Hierarchical Manipulation Planning Framework Combining Striking, Pushing and Pick & Place Motion Primitives}, BOOKTITLE = {International Conference on Automation Science and Engineering}. YEAR = {2024}}
Mobile manipulators find applications in manufacturing, infrastructure inspection, and domestic services.
While most mobile manipulators excel at pick and place, weaim to combine three distinct manipulation primitives: striking,Pushing, and pick-and-place. This integration enables versatile object manipulation and expands the robot’s operational range.
Furthermore, we propose a new attachment that can be easily fitted with most industrial two-finger grippers, capable of
making line contact while pushing or striking an object. The proposed framework includes a high-level action sequence
planner, dedicated offline planners for each manipulation primitive (Strike, Push, and Pick & Place), and a whole-body
controller. Preliminary results from simulations and hardware
experiments demonstrate the potential for diverse applications
in the field of mobile manipulation.
Constrained 6-DoF Grasp Generation on Complex Shapes for Improved
Dual-Arm Manipulation
Gaurav Singh,Kalwar Sanket Hemant,Md Faizal Karim,Bipasha Sen,Nagamanikandan Govindan,Srinath Sridhar,K Madhava Krishna
International Conference on Intelligent Robots and Systems, IROS, 2024
@inproceedings{bib_Cons_2024, AUTHOR = {Gaurav Singh, Kalwar Sanket Hemant, Md Faizal Karim, Bipasha Sen, Nagamanikandan Govindan, Srinath Sridhar, K Madhava Krishna}, TITLE = {Constrained 6-DoF Grasp Generation on Complex Shapes for Improved
Dual-Arm Manipulation}, BOOKTITLE = {International Conference on Intelligent Robots and Systems}. YEAR = {2024}}
Efficiently generating grasp poses tailored to specific regions of an object is vital for various robotic manipulation tasks, especially in a dual-arm setup. This scenario presents a significant challenge due to the complex geometries involved, requiring a deep understanding of the local geometry to generate grasps efficiently on the specified constrained regions. Existing methods only explore settings involving table-top/small objects and require augmented datasets to train, limiting their performance on complex objects. We propose CGDF: Constrained Grasp Diffusion Fields, a diffusion-based grasp generative model that generalizes to objects with arbitrary geometries, as well as generates dense grasps on the target regions. CGDF uses a part-guided diffusion approach that enables it to get high sample efficiency in constrained grasping without explicitly training on massive constraint-augmented datasets. We provide qualitative and quantitative comparisons using analytical metrics and in simulation, in both unconstrained and constrained settings to show that our method can generalize to generate stable grasps on complex objects, especially useful for dual-arm manipulation settings, while existing methods struggle to do so. More results, code and an extended version of the paper can be found on the project page: https://constrained-grasp-diffusion.github.io/
A Novel Hybrid Gripper Capable of Grasping and Throwing Manipulation
Nagamanikandan Govindan,Bharadhwaj Ramachandran,Pasala Haasith Venkata Sai,K Madhava Krishna
IEEE/ASME Transactions on Mechatronics, IEEE/ASME TMECH, 2023
@inproceedings{bib_A_No_2023, AUTHOR = {Nagamanikandan Govindan, Bharadhwaj Ramachandran, Pasala Haasith Venkata Sai, K Madhava Krishna}, TITLE = {A Novel Hybrid Gripper Capable of Grasping and Throwing Manipulation}, BOOKTITLE = {IEEE/ASME Transactions on Mechatronics}. YEAR = {2023}}
Throwing motion is known for phenomenally fast rearrangement, sorting tasks, and placing the object outside the limited workspace with less effort. However, in the robotics domain, despite many simple yet versatile, mechanically intelligent grippers reported earlier, they fo- cus primarily on achieving robust grasping and dexterous manipulation. This article presents a novel design of a sin- gle actuator driven hybrid gripper with mechanically cou- pled rigid links and elastic gripping surface; this arrange- ment provides the dual function of versatile grasping and throwing manipulation. The gripper comprises a latching mechanism (LM) that drives two passive rigid fingers by elongating/releasing the coupled elastic strip. Elongating the gripping surface enables the gripper to adapt to ob- jects with different geometries, vary surface contact force characteristics, and store the energy in the form of elastic potential. A mechanism to discharge the stored potential energy gradually or instantaneously is essential when the intended task is to place the object free from impact or away from the limited reachable workspace. The proposed LM can swiftly shift from a quick release to a gradual release of the stored elastic potential for greater object’s accelera- tion during throwing and no acceleration while placing. By doing so, the object can be placed at the desired location even farther than the manipulator’s reachable workspace. We report the proposed gripper’s design details, develop- ment, and experimentally demonstrate the versatile grasp- ing, impact-free placing, and throwing capabilities. Index Terms—Gripper design, multipurpose gripper, non- prehensile manipulation, throwing.
Predictive Barrier Lyapunov Function Based Control for Safe Trajectory Tracking of an Aerial Manipulator
Vedant Mundheda,Karan Mirakhor,Rahul K S,Harikumar K,Nagamanikandan Govindan
European Control Conference, ECC, 2023
@inproceedings{bib_Pred_2023, AUTHOR = {Vedant Mundheda, Karan Mirakhor, Rahul K S, Harikumar K, Nagamanikandan Govindan}, TITLE = {Predictive Barrier Lyapunov Function Based Control for Safe Trajectory Tracking of an Aerial Manipulator}, BOOKTITLE = {European Control Conference}. YEAR = {2023}}
This paper proposes a novel controller framework that provides trajectory tracking for an Aerial Manipulator (AM) while ensuring the safe operation of the system under unknown bounded disturbances. The AM considered here is a 2-DOF (degrees-of-freedom) manipulator rigidly attached to a UAV. Our proposed controller structure follows the conventional inner loop PID control for attitude dynamics and an outer loop controller for tracking a reference trajectory. The outer loop control is based on the Model Predictive Control (MPC) with constraints derived using the Barrier Lyapunov Function (BLF) for the safe operation of the AM. BLF-based constraints are proposed for two objectives, viz. 1) To avoid the AM from colliding with static obstacles like a rectangular wall, and 2) To maintain the end effector of the manipulator within the desired workspace. The proposed BLF ensures that the above-mentioned objectives are satisfied even in the presence of unknown bounded disturbances. The capabilities of the proposed controller are demonstrated through high-fidelity non-linear simulations with parameters derived from a real laboratory scale AM. We compare the performance of our controller with other state-of-the-art MPC controllers for AM.
A new gripper that acts as an active and passive joint to facilitate prehensile grasping and locomotion
Nagamanikandan Govindan,Shashank Ramesh,Asokan Thondiyath
International Conference on Intelligent Robots and Systems, IROS, 2022
@inproceedings{bib_A_ne_2022, AUTHOR = {Nagamanikandan Govindan, Shashank Ramesh, Asokan Thondiyath}, TITLE = {A new gripper that acts as an active and passive joint to facilitate prehensile grasping and locomotion}, BOOKTITLE = {International Conference on Intelligent Robots and Systems}. YEAR = {2022}}
Among primates, the prehensile nature of the hand is vital for greater adaptability and a secure grip over the substrate/branches, particularly for arm-swinging motion or brachiation. Though various brachiation mechanisms that are mechanically equivalent to underactuated pendulum models are reported in the literature, not much attention has been given to the hand design that facilitates both locomotion and within-hand manipulation. In this paper, we propose a new robotic gripper design, equipped with shape conformable active gripping surfaces that can act as an active or passive joint and adapt to substrates with different shapes and sizes. A floating base serial chain, named GraspMaM, equipped with two such grippers, increases the versatility by performing a range of locomotion and manipulation modes without using dedicated systems. The unique gripper design allows the robot to estimate the passive joint state while arm-swinging and exhibits a dual relationship between manipulation and locomotion. We report the design details of the multimodal gripper and how it can be adapted for the brachiation motion assuming it as an articulated suspended pendulum model. Further, the system parameters of the physical prototype are estimated, and experimental results for the brachiation mode are discussed to validate and show the effectiveness of the proposed design.
Towards Mission-Specific Characterization of the Diving Performance of an Underwater Glider
Siddharth Dey,Ridhi Puppala,Nagamanikandan Govindan,Thiyagarajan Ranganathan,Asokan Thondiyath
@inproceedings{bib_Towa_2022, AUTHOR = {Siddharth Dey, Ridhi Puppala, Nagamanikandan Govindan, Thiyagarajan Ranganathan, Asokan Thondiyath}, TITLE = {Towards Mission-Specific Characterization of the Diving Performance of an Underwater Glider}, BOOKTITLE = {OCEANS}. YEAR = {2022}}
Underwater gliders are common robotic platforms that usually have at least three degrees of freedom (DoF), namely surge, heave, and pitch. The heave motion generated using variable buoyancy can be vectored along surge direction using wings. These gliders are usually designed to be operated for specific applications and the mission dictates the diving requirements, usually quantified using factors such as dive-cycle, dive-in-depth, and range. Several parameters influence diving performance, of which, dimension and position of the wing play a significant role. The objective of this work is to study the effect of wing parameters such as the position of the wing (along the hull) and its dimensions, on the diving performance of the glider and thereby determine their optimal values for a given mission requirement. The wing can be accordingly designed and attached to the hull of the glider. The design and dynamics of RoBuoy, a novel underwater glider, is used for this study. Conveniently RoBuoy’s design allows modular wing positioning and dimensions, and hence the results of the study can be tested on this platform. A detailed study of the influence of the chosen wing parameters on the dynamics of the glider along with a Genetic Algorithm (GA) based approach to optimizing the parameters is presented in this paper.
Modular pipe climber iii with three-output open differential
Vadapalli Sreerama Adithya,Saharsh Agarwal,N VISHNU KUMAR,Kartik Suryavanshi,Nagamanikandan Govindan,K Madhava Krishna
International Conference on Intelligent Robots and Systems, IROS, 2021
@inproceedings{bib_Modu_2021, AUTHOR = {Vadapalli Sreerama Adithya, Saharsh Agarwal, N VISHNU KUMAR, Kartik Suryavanshi, Nagamanikandan Govindan, K Madhava Krishna}, TITLE = {Modular pipe climber iii with three-output open differential}, BOOKTITLE = {International Conference on Intelligent Robots and Systems}. YEAR = {2021}}
The paper introduces the novel Modular Pipe Climber III with a Three-Output Open Differential (3-OOD) mechanism to eliminate slipping of the tracks due to the changing cross-sections of the pipe. This will be achieved in any orientation of the robot. Previous pipe climbers use three-wheel/track modules, each with an individual driving mechanism to achieve stable traversing. Slipping of tracks is prevalent in such robots when it encounters the pipe turns. Thus, active control of each module’s speed is employed to mitigate the slip, thereby requiring substantial control effort. The proposed pipe climber implements the 3-OOD to address this issue by allowing the robot to mechanically modulate the track speeds as it encounters a turn. The proposed 3-OOD is the first three-output differential to realize the functional abilities of a traditional two-output differential.
DESIGN AND ANALYSIS OF THREE-OUTPUT OPEN DIFFERENTIAL WITH 3-DOF
Nagamanikandan Govindan,Rama Vadapalli,K Madhava Krishna
Technical Report, arXiv, 2021
@inproceedings{bib_DESI_2021, AUTHOR = {Nagamanikandan Govindan, Rama Vadapalli, K Madhava Krishna}, TITLE = {DESIGN AND ANALYSIS OF THREE-OUTPUT OPEN DIFFERENTIAL WITH 3-DOF}, BOOKTITLE = {Technical Report}. YEAR = {2021}}
This paper presents a novel passive three-output differential with three degrees of freedom (3DOF), that translates motion and torque from a single input to three outputs. The proposed ThreeOutput Open Differential is designed such that its functioning is analogous to the functioning of a traditional two-output open differential. That is, the differential translates equal motion and torque to all its three outputs when the outputs are unconstrained or are subjected to equivalent load conditions. The introduced design is the first differential with three outputs to realise this outcome. The differential action between the three outputs is realised passively by a symmetric arrangement of three two-output open differentials and three two-input open differentials. The resulting differential mechanism achieves the novel result of equivalent input to output angular velocity and torque relations for all its three outputs. Furthermore, Three-Output Open Differential achieves the novel result for differentials with more than two outputs where each of its outputs shares equivalent angular velocity and torque relations with all the other outputs. The kinematics and dynamics of the Three-Output Open Differential are derived using the bond graph method. In addition, the merits of the differential mechanism along with its current and potential applications are presented.
Design and Analysis of Modular Pipe Climber-III with a Multi-Output Differential Mechanism
N VISHNU KUMAR,Saharsh Agarwal,Rama Vadapalli,Nagamanikandan Govindan,K Madhava Krishna
International Conference on Advanced Intelligent Mechatronics, AIM, 2021
@inproceedings{bib_Desi_2021, AUTHOR = {N VISHNU KUMAR, Saharsh Agarwal, Rama Vadapalli, Nagamanikandan Govindan, K Madhava Krishna}, TITLE = {Design and Analysis of Modular Pipe Climber-III with a Multi-Output Differential Mechanism}, BOOKTITLE = {International Conference on Advanced Intelligent Mechatronics}. YEAR = {2021}}
This paper presents the design of an in-pipe climbing robot that operates using a novel ‘Three-output open differential’(3-OOD) mechanism to traverse complex networks of pipes. Conventional wheeled/tracked in-pipe climbing robots are prone to slip and drag while traversing in pipe bends. The 3-OOD mechanism helps in achieving the novel result of eliminating slip and drag in the robot tracks during motion. The proposed differential realizes the functional abilities of the traditional two-output differential, which is achieved the first time for a differential with three outputs. The 3-OOD mechanism mechanically modulates the track speeds of the robot based on the forces exerted on each track inside the pipe network, by eliminating the need for any active control. The simulation of the robot traversing in the pipe network in different orientations and in pipe-bends without slip shows the proposed design’s effectiveness.
