Abstract: Motion parameters estimation for localization of differential drive vehicles is an important part of robotics and autonomous navigation. Conventional methods require introceptive as well extroceptive sensors for localization. The present disclosure provides a control command based adaptive system and method for estimating motion parameters of differential drive vehicles. The method utilizes information from one or more time synchronized command signals and generate an experimental model for estimating one or more motion parameters of the differential drive vehicle by computing a mapping function. The experimental model is validated to determine change in the one or more motion parameters with change in one or more factors and adaptively updated to estimate updated value of the one or more motion parameters based on the validation. The system and method of present disclosure provide accurate results for localization with minimum use of extroceptive sensors.

Abstract: The disclosure relates to motion planning for autonomous vehicles to find a contiguous path to travel from a source to a destination in a real time environment. But, motion planning suffers due to dimensionality problem during planning a path in high dimensional configuration space. Conventional a priori path planning techniques utilize deterministic selection of a seed and there is a challenge in providing resolution completeness, especially in a cluttered environment. Here, the resolution problem associated with the cluttered environment, is rectified by utilizing random seed generation technique. A convex region is grown around each seed and a set of hyperplanes are generated around each convex region. A contiguous polytope is created by utilizing the set of hyperplanes associated with each convex region. Further, an undirected graph is created based on a plurality of polytope points associated with the contiguous polytope and a shortest path in the graph is computed.

Abstract: This disclosure relates generally to real-time path planning. Planning amidst obstacles in a cluttered indoor environment is a difficult task for a robotic agent. The disclosed method provides semidefinite programming induced free-space based path planning. Free-space is generated by an efficient environment grid resolution independent seeding technique. In the proposed resolution independent seeding technique, initial position of the robotic agent is considered as the first seed. For subsequent seeding, information of the expanded earlier seeds are employed intelligently. This process is followed unto a finite sequence, which naturally results in a contiguous navigable convex free-space. This contiguous navigable convex free-space is employed to create an undirected graph, which is then used for path planning. Path planning is done locally by evaluating the subgoal with respect to a final goal. Local planning cumulatively assists the planner to attain the final goal.

Abstract: An auction-based bid generation technique is a NP-hard problem and is not suitable for real-time scheduling of multi-agents. The embodiments thus provide a system and method for scheduling a set of tasks among a plurality of agents. Herein, agents self-allocate tasks among themselves dynamically in a distributed fashion, following an ordered sequence of agent indexes. The motivation of following the ordered sequence of agent indexes is allowing each agent to select its best strategy once by exploiting the greedy characteristic of the agent. The preferred agent (based on the ordered sequence) self-allocates tasks among multiple based on the minimum L2 Norm between task attributes and agent attributes, results in a strategy. The strategy offered by a sequence needs to satisfy constraints. A heuristic reward function for each strategy is proposed. Based on these rewards, agents reach consensus by playing an exact potential game for scheduling tasks among the agents.

Abstract: Robots are used extensively in different applications so as to perform specific tasks. However, the robots are required to move around in a location where they are present, so as to perform the tasks. For path planning, free space identification is performed by the robots during which obstacles are detected and free space is identified. However, the existing systems for path planning struggle to identify free space in cluttered environments. The disclosure herein generally relates to robotic path planning, and, more particularly, to a method and system for free space detection in a cluttered environment for robotic path planning. The system inscribes obstacles in bounding boxes and all unit grids inscribed by the bounding boxes are considered as occupied. Further, by seeding the occupancy grid map, the system identifies unified segments and corresponding seeds. Further a convex expansion is executed in the occupancy grid map to detect the free space.

Abstract: This disclosure relates generally to real-time path planning. Planning amidst obstacles in a cluttered indoor environment is a difficult task for a robotic agent. The disclosed method provides semidefinite programming induced free-space based path planning. Free-space is generated by an efficient environment grid resolution independent seeding technique. In the proposed resolution independent seeding technique, initial position of the robotic agent is considered as the first seed. For subsequent seeding, information of the expanded earlier seeds are employed intelligently. This process is followed unto a finite sequence, which naturally results in a contiguous navigable convex free-space. This contiguous navigable convex free-space is employed to create an undirected graph, which is then used for path planning. Path planning is done locally by evaluating the subgoal with respect to a final goal. Local planning cumulatively assists the planner to attain the final goal.

Abstract: Motion parameters estimation for localization of differential drive vehicles is an important part of robotics and autonomous navigation. Conventional methods require introceptive as well extroceptive sensors for localization. The present disclosure provides a control command based adaptive system and method for estimating motion parameters of differential drive vehicles. The method utilizes information from one or more time synchronized command signals and generate an experimental model for estimating one or more motion parameters of the differential drive vehicle by computing a mapping function. The experimental model is validated to determine change in the one or more motion parameters with change in one or more factors and adaptively updated to estimate updated value of the one or more motion parameters based on the validation. The system and method of present disclosure provide accurate results for localization with minimum use of extroceptive sensors.

Abstract: The disclosure relates to motion planning for autonomous vehicles to find a contiguous path to travel from a source to a destination in a real time environment. But, motion planning suffers due to dimensionality problem during planning a path in high dimensional configuration space. Conventional a priori path planning techniques utilize deterministic selection of a seed and there is a challenge in providing resolution completeness, especially in a cluttered environment. Here, the resolution problem associated with the cluttered environment, is rectified by utilizing random seed generation technique. A convex region is grown around each seed and a set of hyperplanes are generated around each convex region. A contiguous polytope is created by utilizing the set of hyperplanes associated with each convex region. Further, an undirected graph is created based on a plurality of polytope points associated with the contiguous polytope and a shortest path in the graph is computed.

Abstract: Robots are used extensively in different applications so as to perform specific tasks. However, the robots are required to move around in a location where they are present, so as to perform the tasks. For path planning, free space identification is performed by the robots during which obstacles are detected and free space is identified. However, the existing systems for path planning struggle to identify free space in cluttered environments. The disclosure herein generally relates to robotic path planning, and, more particularly, to a method and system for free space detection in a cluttered environment for robotic path planning. The system inscribes obstacles in bounding boxes and all unit grids inscribed by the bounding boxes are considered as occupied. Further, by seeding the occupancy grid map, the system identifies unified segments and corresponding seeds. Further a convex expansion is executed in the occupancy grid map to detect the free space.