Nishanth Adithya Chandramouli

I am currently pursuing my Master’s degree in Robotics Engineering at Worcester Polytechnic Institute(WPI) where I am engaged in directed research under the guidance of Prof. Nitin Sanket and Prof. Connor McCann in the Perception and Autonomous Robotics ( PeAR) Lab. My research at WPI focuses on developing soft drone shells and corresponding computational control methods in parallel to enhance stability and performance during collisions

Prior to my graduate studies, I worked as a Project Associate in the Robotics Lab at Indian Institute of Technology Madras with Prof. Sandipan Bandyopadhyay. During this time, my research concentrated on the computational design and singularity analysis of parallel manipulators. I received my Bachelors in Mechanical Engineering from SASTRA University in September 2023.


2019 - 2023
2023 - 2025
2025 - Current



Research Interests: My research interests lie at the intersection of mechanics and artificial intelligence. I aim to integrate reinforcement learning with motion planning to achieve general-purpose robotic autonomy.


Publications


Multi objective path planning for the 6-6 Stewart platform manipulator using the singularity free tube

Nishanth Adithya Chandramouli

,

Aditya Mahesh Kolte, Shashank Ramesh, Sandipan Bandyopadhyay*

IPRoMM 2024

Paper

A multi objective approach for constant-orientation singularity-free path planning for the 6-6 semi-regular Stewart platform manipulator (SRSPM) is presented in this paper. The concept of the singularity-free tube (SFT), which is described as a one-parametric family of singularity-free spheres, is utilised to ensure that the obtained paths are free of any gain-type singularities. NonDominated Sorting Genetic Algorithm (NSGA-II) is used to obtain a set of optimal paths connecting two given points while minimising its length and maximising its distance from the boundary of the SFT.

A Semi-Analytical Approach Towards Determining the Largest Collision-Free Sphere in R3 Inside the Effective Regular Workspace of a 6-6 Stewart-Gough Platform Manipulator Corresponding to a Given Orientation Workspace

Bibekanandha Patra,

Nishanth Adithya Chandramouli

,

Sandipan Bandyopadhyay*

Mechanisms and Machine Theory

Paper

This article focusses on the problem of interference among the links of a parallel robot, namely, the StewartGough platform manipulator. The geometry of the legs is approximated by capsules, leading to the detection of collision among any pair of legs in terms of tangency of the corresponding capsules. Analytical conditions for the said cases of tangency are derived in closed-form, which manifest geometrically as certain quadrics in space. Through a thorough study and explicit characterisation of these surfaces, novel analytical methods are developed to find the largest spheres in space which are tangent to these surfaces. Such spheres are free of possibilities of link collisions, and they can be derived analytically for a given orientation of the moving platform of the manipulator. The analysis is subsequently extended to the orientation workspace of the manipulator by repeating the above-mentioned computations over a large number of discrete samples. The results obtained are verified numerically by comparing them with those generated from other sources. A parametric study is performed to demonstrate the utility of the proposed analysis in practice.

A comprehensive analysis of the spherical joint in a 6-6 Stewart-Gough platform manipulator and its effects on the joint limit compliant workspace

Bibekanandha Patra, Shivani Guptasarma,

Nishanth Adithya Chandramouli

,

Sandipan Bandyopadhyay*

NeurIPS 2023

Paper / Code (Coming Soon) / Video

We propose HyP-NeRF, a latent conditioning method for learning generalizable category-level NeRF priors using hypernetworks. We use hypernetworks to estimate both the weights and the multi-resolution hash encodings resulting in significant quality gains. To further improve quality, we incorporate a denoise and finetune strategy that denoises images rendered from NeRFs estimated by the hypernetwork and finetunes it while retaining multiview consistency.

Disentangling Planning and Control for Non-prehensile Tabletop Manipulation

Vishal Reddy Mandadi, ...,

Aditya Agarwal

, ..., Madhava Krishna

CASE 2023

Paper (Coming Soon)/ Video (Coming Soon)

We propose a framework that disentangles planning and control for tabletop manipulation in unknown scenes using a pushing-by-striking method (without tactile feedback) by explicitly modeling the object dynamics. Our method consists of two components: an A* planner for path-planning and a low-level RL controller that models object dynamics.



News & Announcements



Academic Services

  • Reviewer for ICRA 2024, CVPR 2024.

  • Reviewer for SIGGRAPH 2023, IROS 2023, ICLR 2023 workshops, ICRA 2023.

  • [Aug '22] Coordinator for the 6th CVIT Summer School on AI.

  • [Aug '22] Gave a talk on the challenges in tabletop rearrangement and planning at CVIT Summer School 2022.

  • [Feb '22] I will be taking month long tutorial sessions in machine learning for faculties across universities in India as part of the CSEDU-ML program conducted jointly by IIIT-H, IIT-H, and IIT-D.

  • [Aug '21] Coordinator for the 5th CVIT Summer School on AI and conducted tutorial sessions on self-supervised learning and multimodal learning.


Professional Achievements


Forked and modified from Viraj Prabhu's adaptation of Pixyll theme