Department Publications

Humanoid robots have become increasingly popular in applications such as social interaction, education, and service roles, which drives the need for more natural and efficient human-robot interactions. However, currently available humanoid heads often face limitations, including high costs, mechanical complexity, and limited adaptability across diverse environments. To address these challenges, we present an articulated humanoid robot head designed for a receptionist role, integrating a mechanical structure with 21 degrees of freedom (DoF), including mechanisms for the mouth, eyes, eyebrows, and neck, and covered with realistic silicone skin to achieve a human-like appearance and expression. The system integrates a model-based architecture that combines SCRFD, ArcFace, and ByTetrack for face recognition and Llama and Whisper for natural language processing, with hardware support enabling real …

Trajectory planning strongly influences tracking accuracy, actuator demand, and overall execution behavior in robotic manipulators. Classical planners such as cubic, quintic, and trapezoidal profiles are widely used for their simplicity and smoothness, yet they remain purely kinematic and ignore system dynamics and control effort during trajectory generation. As a result, nominally smooth trajectories can lead to inefficient nonlinear execution and increased corrective control action. This paper presents a control-aware optimal trajectory planning framework that explicitly incorporates manipulator dynamics and actuator effort within a finite-horizon formulation. A midpoint linearization strategy is introduced to improve approximation accuracy for large point-to-point motions. In contrast to prior comparisons, the proposed approach enables fair, isolated evaluation of trajectory generation effects under identical closed-loop nonlinear execution conditions. To this end, a unified evaluation framework is developed in which all planners are executed under identical nonlinear dynamics, controller structure, and actuator constraints. Simulations on a nonlinear simplified UR5 manipulator show that the proposed approach consistently reduces tracking error, corrective torque, and closed-loop execution cost compared to classical methods, achieving substantial reductions in actuator effort and execution cost across all evaluated scenarios, demonstrating that kinematic smoothness alone does not ensure dynamically efficient execution.

A sense of independence is critical for individuals with mobility impairments, with stair negotiation remaining one of the most demanding daily tasks. This article presents a novel track-based stair-climbing mechanism inspired by leech locomotion, designed to enhance adaptability to varying staircase geometries. The mechanism emulates leech-like motion during both ascent and descent, decomposing each maneuver into multiple segments to ensure stable posture and safety. Throughout motion, the mechanism maintains a large contact surface with the stairs, improving stability. Simulation and experimental studies validate the effectiveness of the proposed motion, particularly during transitions at the top and bottom of the staircase. Results demonstrate that the motion profile reduces abrupt movements and improves user comfort during stair-climbing operation.

Solar photovoltaic (PV) systems have become a trend as a sustainable energy source on a global scale. However, the dirt accumulated on solar panels often reduces their efficiency, considerably. Existing cleaning methods have limitations such as requiring manual labour, low efficiency, limited to single cleaning method or single operational mode. As a solution, this research study describes the design and implementation of a semi-autonomous solar panel cleaning robot for both dry and wet cleaning. The robot can autonomously navigate on solar panels safely, or user can manually control it using a mobile app. The robot is capable of functioning for around 75 minutes on a single charge on solar panels tilted up to 20°, facilitated by image processing algorithms achieving an accuracy surpassing 96%. The orientation estimation is accomplished through the implementation of three parallel Kalman filters running on …

Image generation from a single image using generative adversarial networks is quite interesting due to the realism of generated images. However, recent approaches need improvement for such realistic and diverse image generation, when the global context of the image is important such as in face, animal, and architectural image generation. This is mainly due to the use of fewer convolutional layers for mainly capturing the patch statistics and, thereby, not being able to capture global statistics very well. We solve this problem by using attention blocks at selected scales and feeding a random Gaussian blurred image to the discriminator for training. Our results are visually better than the state-of-the-art particularly in generating images that require global context. The diversity of our image generation, measured using the average standard deviation of pixels, is also better.

This paper introduces a novel locomotion strategy of combining wheeled and legged actuation in a parallel structure. This enables the robot to traverse rough terrains using the articulated limbs and use wheeled locomotion for more efficient traversal over smooth terrains. Authors present a prototype robot architecture to embody the concept and show experimentally the robot traversing a variety of indoor and outdoor terrains. Additionally, a novel butterfly gait is introduced for the robot that enables stable and efficient traversal of challenging terrains.

This research paper presents a novel track based stair-climbing wheelchair design with improved stability and performance. The proposed design has an adaptable arrangement to the staircase especially at the top of the staircase. In the existing wheelchair designs, this particular feature has not been adequately addressed. The proposed design consists of body frame and supporting rubber track arms. Of the two main operations; ascending and descending, the most critical operations is at the top of the staircase, which is smoothly controlled by following the staircase profile. This motion is achieved by properly synchronizing the rubber track arms according to a pre-planned motion profile. As a result, user does not feel sudden motions in position and attitude. Furthermore, the proposed wheelchair is adaptable to any staircase.

Reinforcement learning algorithms have been successfully trained for games like GO, Atari, and Chess in simulated environments. However, in cue sport-based games like Carrom, real world is unpredictable unlike in Chess and GO due to the stochastic nature of the gameplay as well as the effect of external factors such as friction combined with multiple collisions. Hence, solely training in a simulated platform for games like Billiard and Carrom, which need precise execution of a shot, would not be ideal in actual gameplay. This paper presents a real-time vision based efficient robotic system to play Carrom against a proficient human opponent. We demonstrate the challenges of adopting a reinforcement learning algorithm beyond simulations in implementing a strategic gameplay for the robotic system. We currently achieve an overall shot accuracy of 70.6% by combining heuristic and reinforcement learning …

Travelling along routine paths on foot is an exhausting and mundane task. Current personal mobility vehicles (PMVs), which address this issue, are driven manually and are too heavy to be carried by the user when needed. As a solution to this, an autonomous, self-balancing, lightweight, compact and low-cost PMV is developed. The device is capable of simultaneously self-balancing and navigating autonomously in an indoor environment. Moreover, it can be manually controlled using the developed smart mobile phone application. Self-balancing, localization, navigation and obstacle avoidance are achieved in real time using on-board sensors and processing units. Systematic experiments are carried out with the developed PMV in typical indoor environments in order to assess the robustness of the above features. The results show that the robot is able to successfully achieve its navigation tasks both with and …

The widespread use of high definition cameras for surveillance and related tasks has given rise to the concept of edge computing as transmitting and processing video streams in real time have become challenging. However, edge computing at low power and lower cost is difficult with general purpose processor hardware inside cameras. Finding a solution that meets the above requirements and demonstrates flexibility to handle diverse conditions is challenging. In this paper, we propose a coprocessor architecture which is specifically designed to perform machine vision related operations at the edge using very long instruction word (VLIW) architecture. It also supports multiple vision algorithms in the same hardware platform while supporting runtime reconfigurability, architectural flexibility, and extensibility. The system was practically realized on ZedBoard and verified for correct functionality and accuracy at 148.5 …

Personal and medium scale farming has been showing a downward trend throughout the past few decades. Individuals are demotivated to engage in farming activities, due to lack of time, and the higher efficiency in large-scale farming. However, there is a significant health concern arising from the consumption of these products, as they are grown using artificial fertilizers and contain residues of insecticides and pesticides. Automation can motivate personal and medium scale farming, through cutting down the time requirements for farming and by increasing the farming efficiency. Our solution - Scalable Autonomous Agronomical Smartbot (SAASbot) aims at automating farming activities (planting seeds, watering, fertilizing, weed removal) while providing a scalable robotic platform for personal to medium scale farming. In this paper, design and implementation of the SASSBot and testing and validation of the system …

Voice commands have been used as the basic method of interaction between humans and robots over the years. Voice interaction is natural and require no additional technical knowledge. But while using voice commands humans frequently use uncertain information. In the case of object manipulation on a table, frequently used uncertain terms “Left,“Right”,“Middle”,“Front”... etc. These terms fail to depict an exact location on the table and the interpretation is governed by the robots point of view. Depending solely on vocal cues is not ideal as it requires the users to explain the exact location with more words and phrases making the interaction process cumbersome and less human like. However, using hand gestures to pinpoint the location is as natural as using the voice commands and frequently used when manipulating items on a surface. When compared to voice commands use of hand gestures is a more direct and less cumbersome approach. But when used alone hand gestures can result in errors while extracting the pointed location making the user dissatisfied. This paper proposes a multi-modal interaction method which uses hand gestures combined with voice commands to interpret uncertain information when placing an object on a table. Two fuzzy inference systems have been used to interpret the uncertain terms related to the two axes of the table. The proposed system has been implemented on an assistive robot platform. Experiments have been conducted to analyze the behaviour of the system.

Large debris created after natural disasters restrict access to inner parts of affected regions and slows down disaster relief operations. Power shovels are often used to clear wreckage but the process can take a lot of time. Moreover, it is dangerous to involve human workers in such conditions due to loose debris collapsing and causing severe damage. To speedup access to inner areas, instead of removing obstacles, they can be surmounted with the assistance of a carefully maneuvered power shovel arm. In this paper, an autonomous obstacle surmounting technique for an unmanned power shovel is proposed. Out of different sequences, the one that optimizes the total energy consumption is selected as the best candidate for surmounting a given obstacle by dynamic simulations. The experiments conducted using a miniaturized power shovel show the effectiveness of the proposed method.

Large debris created after natural disasters restrict access to inner parts of affected regions, and slows down disaster relief operations. Power shovels are often used to clear wreckage but the process can take a lot of time. Moreover, it is dangerous to involve human workers operating heavy machinery in such unstable conditions. To speedup access to inner areas, obstacles can be surmounted with the assistance of carefully maneuvered power shovel arm, instead of removing them. In this work, an autonomous obstacle surmounting technique for an unmanned power shovel is proposed. Out of different sequences, the one that optimizes the total energy consumption is chosen as the best candidate for surmounting a given step-like obstacle. Dynamic simulation results show the effectiveness of the proposed method.

Power shovels are used to clear wreckage after natural disasters but the process can consume a lot of time. Furthermore, operating such heavy machines in those circumstances is very dangerous for the involved human workers. To speed up access to inner parts of disaster stricken areas, obstacles can be surmounted with the assistance of carefully maneuvered arm, instead of removing them. In this paper, an autonomous obstacle surmounting technique for an unmanned power shovel is proposed. Out of different sequences, the one that optimizes the total energy consumption is chosen as the best candidate for surmounting a given step-like obstacle. Simulation and experiment results show the effectiveness of the proposed method.

A new trajectory planning method for generating bounded and continuous jerk trajectories in joint space has been developed and tested. In manipulator trajectory planning, reduced jerk trajectories are desired for path tracking and vibration suppression. The proposed interpolation algorithm in this research generates a spline, composed with 5th-order, 3rdorder and 5th-order polynomial segments (5-3-5 spline) which can be used for point-to-point trajectories and trajectories with via points. The generated trajectories are continuously differentiable in position, velocity, acceleration, and has a start and end zero bounded continuous jerk profile. The algorithm allows the user to independently define the position, velocity, acceleration and jerk values at both start and end points, via point positions and velocities. These user definable parameters in the proposed 5-3-5 spline algorithm gives the flexibility for generating …

Tunable laser system requires high resolution and accuracy in position of the wave selective optical element, which can be attained through the use of stepper motor. This paper focuses on the stepper motor controller, with the feedback to improve the accuracy and the microstepping technique to improve the resolution. Sine cosine and trapezoidal current controlling techniques for the micro stepping are used in two different types of situations. The proposed controller uses the linear interpolation and sine cosine current controlling technique to double the rotation accuracy than the resolution of the encoder and detect the obstacle by using the encoder and the static characteristic of the stepper motor. Also, the variable step interval technique is proposed to overcome the speed variation in the trapezoidal current controlling technique. The simulation and the experimental results show that, proposed controller can …

In this paper, we present a novel strategy to detect the slipping of an object grasped by a human hand. The recognition of slipping of a grasped object early plays a significant role in designing the dexterous robotic hands to ensure a firm grasping. Here, we present a system that uses force sensors embedded in a tight glove to capture force variations during a slipping of a grasped object. The analysis of contribution by five fingers and the palm for grasping is presented based on new factor called contribution factor. Also, we propose a new direction to incorporate controlling of dexterous robot hands based on spatial activity of force exerted by hand to ensure a firm grasping.

In this work, we propose a framework that can provide performance metrics with regards to the usability of an assistive device designed to provide visual servoing of a reaching task performed by a visually impaired individual. The framework provides a model and methodology from which performance metrics can be synthesized based on robotic manipular kinematics and an adaptation of Fitts' law for reaching task motions in a 3D environment. The purpose of which is to facilitate an understanding of how well the system's design accommodates the user's natural movement style when performing the reaching task. Use of advances in visual tracking techniques employing scale, view-point, and illumination invariant features are incorporated to allow for a further decoupling of the feature space from the joint-level control space.

A new type of force-position compliant control is proposed, where hyperbolic tangent function is used to dynamically adjust the gain of the position feedback loop so that to control the contact force safely and according to a given pattern. The proposed compliant controller uses a high gain in the position control loop when the robotic device is in free space motion, and as and when it comes into contact with the environment, the gain of the position loop is lowered according to the roll-off of inverse tangent function. The controller is tunable with only one parametery, and is capable of mimicking a wide range of force control behaviors. In this paper we apply the proposed controller to mimic human compliant motion in gripping and lifting objects. And, we have verified that the human compliant behavior can be satisfactorily realized by the proposed compliant controller.

Industrial robot manipulators are used in various applications in order to achieve fast, precise, and quality production. In pick-and-place operations such as part handling, assembly, etc., the end-effector of the manipulator has to travel between two specific points in the workspace, and the path it takes in between is of no concern. In trajectory tracking applications such as welding, cutting, painting, etc., the end-effector has to follow a specific trajectory in 3-space as closely as possible, while maintaining rated velocity as much as possible (Munasinghe, 2001). In the latter case, planning the trajectory can be complex when there are constraints on the end-effector velocity, joint acceleration, and trajectory error. Trajectories planned without proper consideration to these constraints often result in poor performance such as trajectory overshoots, end-effector deviations from the planned trajectory, and undue velocity fluctuations (Nakamura, et. al., 2000). Performance could be even more deteriorated especially at sharp corners in the Cartesian trajectory (Nakamura, 20001). Lot of trajectory planning algorithms have been proposed so far starting from simple Cartesian path control (Paul, 1979) to time optimized trajectories (Shin, 1985). However, the industrial systems experience difficulties accommodating most of these methods because of at least two specific reasons; 1) These techniques often require hardware changes in the existing setup and the manufacturing process has to be interrupted for system reconfigurations, which usually takes a longer period of time, and 2) Many of these methods often consider only one constraint, and often they pay less …

In this paper the design and implementation of a camera platform that can mimic the neck and the eye movements of humans is presented. The camera platform is intended for active vision applications. It has seven mechanical degrees of freedom corresponding to the degrees of freedom of the human visual system

In this work, we have taken the first step towards the creation of a computerized seeing-eye guide dog. The system we presented extends the development of assistive technology for the visually impaired into a new area: object tracking and visual servoing. The system uses computer vision to provide a kind of surrogate sight for the human user; sensing information from the environment and communicating it through haptic signalling. Our proof-of concept prototype is a low-cost wearable system which uses a colour camera to analyze a scene and recognize a desired object, then generate tactile cues to the wearer to steer his or her hand towards the object. We have proved the system in trials with random users in an unstructured environment.

In this paper the design and implementation of a microprocessor for motion control for a Mobile Stereo Camera Platform for Active Vision, is presented. The Stereo Camera Platform has seven degrees of freedom which can simulate neck and eye movements of humans. The microprocessor interprets the instructions given by the user, does the relevant calculations and drives the seven degrees of freedom of the camera platform. The microprocessor was implemented on FPGA using Verilog hardware description language.